Total 59 job vacancies by Unison Consulting Pte Ltd

• Continuous Service Improvement: Add value to Data Centre Operations by identifying improvement opportunities to sharpen Production stability, stakeholders experience and overall service quality.

• Identifying opportunities for automation within production processes to streamline operations and reduce manual intervention.

• Timely escalation and communication of major incidents such as escalation matrix, leading, driving, facilitating, and chairing all investigation activities.

• Being accountable for resolving the incident with workaround or permanent solution.

• Participate in troubleshooting system and network connectivity problems before escalation.

• Monitoring production metrics and performance indicators to ensure targets are met.

• Ensuring compliance with safety and regulatory standards in production.

• Other ad-hoc duties as instructed.

Good years of IT experience as Level 1 Production Operations engineer.

• Strong analytical skills: The ability to analyse production processes and identify areas for improvement and optimisation.

• Technical Proficiency: Profound knowledge of production systems issues and effective solutions to enhance operation efficiency.

• Problem-Solving Aptitude: A knack for troubleshooting production issues and devising effective solutions to enhance operational efficiency.

• Experience in Data Centre facilities, including temperature and humidity monitoring system, smoke detection and fire suppression systems, Uninterrupted Power Supply (UPS) units, CCTC, keypress units, etc. • Familiarity with AWS tools such as CloudWatch, Cloud Trail, etc would be an advantage.

• Able to work shift duties. -The shift hours are as follow:

▪ 1st shift - 7:00 am to 3:00 pm

▪ 2nd shift - 2:45 pm to 10:30 pm

▪ 3rd shift - 10:15 pm to 07:15 am

o The 8-day rotational shift pattern is as below:

▪ Two days 1st shift, followed by

▪ Two days 2nd shift, followed by

▪ Two days 3rd shift, followed by

▪ Two off days.

• Design, develop, and maintain scalable data pipelines and ETL processes using Hadoop and Spark.
• Write efficient and optimized data processing jobs in Scala to transform and load data.
• Utilize SQL for querying and manipulating data across various databases.
• Collaborate with data scientists and analysts to gather requirements and deliver data solutions that meet business needs.
• Monitor and troubleshoot data processing workflows to ensure high performance and reliability.
• Implement best practices for data quality, governance, and security.
• Document data engineering processes, workflows, and architecture for team knowledge sharing.
• Stay updated on industry trends and emerging technologies to continuously improve our data strategies.

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a Data Engineer or in a similar role.
• Strong proficiency in Hadoop ecosystem components (e.g., HDFS, Hive, Pig).
• Hands-on experience with Apache Spark for big data processing.
• Proficient in Scala programming for data transformation tasks.
• Advanced SQL skills for querying and managing large datasets.
• Experience with data modeling, data warehousing, and ETL processes.
• Familiarity with cloud platforms (AWS, GCP, or Azure) is a plus.
• Strong analytical and problem-solving skills.

• Assist in the development and optimization of ETL processes using PySpark and Databricks.
• Collaborate with team members to design and implement data models and architecture in AWS.
• Maintain and monitor data pipelines to ensure data quality and reliability.
• Utilize GitHub for version control and collaboration on codebases.
• Participate in code reviews and contribute to best practices in coding and data engineering.
• Support the team in implementing CI/CD practices for data workflows.
• Document processes and workflows for data engineering tasks.

• Familiarity with AWS services (e.g., S3, Redshift, Glue) and cloud computing concepts.
• Basic knowledge of Databricks and PySpark for data processing.
• Understanding of Git and experience with GitHub for version control.
• Awareness of DevOps principles and tools (e.g., CI/CD, Docker) is a plus.
• Databricks certification is a plus.

We are seeking an experienced Data Engineer with a strong background in Hadoop, Spark, and SQL, specifically within the banking sector. The ideal candidate will be responsible for designing, building, and maintaining large-scale data pipelines and platforms to support critical banking applications and decision-making processes.

Key Responsibilities:

• Data Pipeline Development: Design, develop, and maintain efficient data pipelines and workflows using Hadoop and Spark frameworks to support the bank’s data processing needs.
• Data Integration & ETL: Create ETL processes to extract, transform, and load large datasets into Hadoop ecosystems from various banking systems, ensuring data consistency and accuracy.
• Database Management: Write optimized SQL queries to manage and analyze data stored across relational databases, data lakes, and cloud platforms.
• Data Processing & Analysis: Implement scalable data processing solutions to analyze large datasets, provide insights, and deliver solutions for financial services and risk management.
• Collaboration: Work closely with business analysts, data scientists, and IT teams to ensure data solutions align with banking sector needs, including compliance with regulations and reporting requirements.
• Performance Optimization: Fine-tune Hadoop and Spark applications for performance, improving throughput and reducing latency.

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Strong years  experience as a Data Engineer, specifically within the banking or financial sector.
• Proficiency in Hadoop ecosystem tools (HDFS, Hive, HBase) and Spark for large-scale data processing.
• Strong experience with SQL and relational databases such as PostgreSQL, MySQL, or Oracle.
• Familiarity with cloud platforms (AWS, Azure) and containerization tools (Docker, Kubernetes) is a plus.
• Experience in data governance and compliance regulations within the financial industry.
• Excellent problem-solving and analytical skills.

• Salary: SGD 6000 - 9500
• Great Work Culture
• Includes comprehensive insurance for self and family. Includes Specialist and Dental Coverage.
• Includes Standard Annual and Sick Leave

• Analyse the Authority’s data needs and document the requirements.
• Refine data collection/consumption by migrating data collection to more efficient channels.
• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.
• Develop test plan and scripts for system testing, support user acceptance testing.
• Work with the Authority’s technical teams to ensure smooth deployment and adoption of new solution.
• Ensure the smooth operations and service level of IT solutions.
• Support production issues.
• Good understanding and completion of projects using waterfall/Agile methodology.
• Hands-on experience in DevOps deployment and data virtualisation tools like Denodo will be preferred.
• Understanding of reporting or visualization tool like SAP BO and Tableau is important.
• Track record in implementing systems using Hive, Impala and Cloudera Data Platform will be preferred.
• Hands-on experience in big data engineering jobs using Python, Pyspark, Linux, and ETL tools like Informatica.
• Strong SQL and data modelling and data analysis skills.
• Good understanding of analytics and data warehouse implementations.
• Ability to troubleshoot complex issues ranging from system resource to application stack traces.
• Track record in implementing systems with high availability, high performance, high security hosted at various data centres or hybrid cloud environments will be an added advantage.

As a Data Engineer specializing in Data Mapping & ETL, you will play a crucial role in designing and implementing data solutions that ensure efficient and accurate data movement across systems. Your responsibilities will include:

• Developing and maintaining ETL processes for data extraction, transformation, and loading.
• Conducting data mapping to transform data across multiple systems and formats.
• Collaborating with data architects and other stakeholders to understand data requirements.
• Optimizing ETL processes for performance and reliability.
• Conducting data quality assessments and implementing data validation techniques.
• Documenting ETL processes and best practices for future reference.

This role will require a blend of technical expertise and analytical skills to manage complex data flows effectively.

To be successful in this role, you should meet the following requirements:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 4+ years of experience in ETL development and data mapping.
• Strong proficiency in SQL and experience with databases such as Oracle, Postgres, or SQL Server.
• Experience with ETL tools such as Apache NiFi, Talend, or AWS Glue.
• Familiarity with data warehousing concepts and dimensional modeling.
• Knowledge of data quality frameworks and data governance principles.
• Proficient in scripting languages like Python or Shell.
• Ability to work in an Agile environment and collaborate with cross-functional teams.
• Preferred : Immediate joiner or max 1 Month

• Design, implement, and maintain ETL processes to extract data from multiple sources, transform it based on business rules, and load it into target systems.
• Develop and manage data mapping documentation, including source-to-target mappings and transformation logic.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and optimize data flows.
• Conduct data quality checks and validation to ensure the accuracy and integrity of data.
• Optimize ETL workflows for performance, scalability, and reliability.
• Monitor and troubleshoot ETL processes, resolving issues promptly to minimize downtime.
• Stay up-to-date with industry best practices and emerging technologies in data engineering and ETL.

• Proven experience as a Data Engineer, with a strong focus on data mapping and ETL processes.
• Strong SQL skills and experience with relational databases (e.g., MySQL, PostgreSQL, Oracle).
• Familiarity with data warehousing concepts and architecture.

Key Responsibilities:

·        Develop and maintain the user interface using React/UI for a seamless user experience.

·        Work with Python (preferred) or Java for backend development.

·        Handle email communication systems using SMTP.

·        Design and implement APIs using Swagger, REST, or SOAP protocols.

·        Manage the server-side environment with expertise in Unix/Linux.

·        Log and monitor applications using Elastic logging (ELK).

·        Work with databases like MongoDB or PostgreSQL for efficient data management.

·        Utilize Postfix for managing email services and configurations.

·        Collaborate with teams to ensure software aligns with banking/financial industry requirements.

Skills Required:

·        Front-End: React/UI

·        Back-End: Python or Java

·        SMTP, API Development (Swagger, REST, SOAP)

·        Unix/Linux experience required

·        ELK Stack (Elastic Logging)

·        Database: MongoDB or PostgreSQL

·        Postfix

·        Functional Understanding of Banking/Financial Systems

We are looking for a strong DevOps candidate to join our DevOps team which manages our DevSecOps infrastructure and works with application teams to automate software deployments. Other than BAU work, the team also works on projects to enhance, optimize and transform the infrastructure.

Key Responsibilities

• Coding and developing new DevOps scripts automation with CI/CD pipelines through Jenkins, Cloudbees, Bitbucket, etc

• Supporting and maintaining full stack DevOps toolsets. (Jira, Confluence, Bitbucket, Cloudbees, Jenkins, SonarQube, Nexus IQ, Fortify)

• Able to code, script, automate, innovate full DevOps automation capabilities to enhance and elevate automation from manual human tasks

• Always able to find ways to automate, develop scripts, innovate new ideas to reduce human work and repetitive tasks.

• Deep knowledge on DevOps tools API automation capabilities

• Troubleshoot, deep dive RCA and fix DevOps platform issues

• Supporting DevOps toolsets running on AWS, container clusters and Kubernetes.

What we are looking for

• Deep experience as a DevOps or DevSecOps practitioner in a critical Production environment
• Deep technical experience in server-side Unix/Linux/PowerShell scripting
• Prior working experience installing, configuring, integrating, upgrading and patching CI/CD toolset
• Prior experience is customizing JIRA and Setting up confluence spaces.
• Passionate about cloud infrastructure, CI/CD pipelines and automation
• Ability to easily pick up new technologies: you are keen to learn and to expand your knowledge
• Customer centricity: you always go above and beyond to deliver a first-class service to your users
• Highly proficient with Linux Systems Administration and network fundamentals (IPv4, TCP, UDP, DNS, HTTP, TLS, routing, load-balancing)
• Proficient with AWS VPC, EC2, IAM, S3, EKS, EFS
• Proficient with ELK, Grafana and Ansible
• Proficient with Terraform, Docker/containers and Kubernetes

We are seeking a skilled and motivated Data Engineer with expertise in Hadoop, Spark, OpenShift Container Platform (OCP), and DevOps practices. As a Data Engineer, you will be responsible for designing, developing, and maintaining efficient data pipelines, processing large-scale datasets. Your expertise in Hadoop, Spark, OCP, and DevOps will be crucial in ensuring the availability, scalability, and reliability of our ML Solutions.

Responsibilities:

•  Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives
• Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions
• Ensure data quality and integrity throughout the data processing lifecycle
• Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques
• Optimize data engineering workflows for containerized deployment and efficient resource utilization
• Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability
• Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance
• Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements
• Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference
• Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps
• Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities .

• Proven 4+ Years of experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments
• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
• Experience with Graphana, Prometheus, Splunk will be an added benefit
• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus

As a Lead ML Engineer, you will play a leading role in operationalizing ML Models developed by Client data scientists. You will serve as the focal point for ML model refactoring, optimization, containerization, deployment, and quality monitoring. Your main responsibilities will include:

• Conduct reviews for compliance of the ML models in accordance with overall platform governance principles such as versioning, data / model lineage, code best practices and provide feedback to data scientists for potential improvements
• Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain. This can include monitoring for data drift, triggering model retraining and setting up rollbacks.
• Optimize AI development environments (development, testing, production) for usability, reliability and performance.
• Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications (e.g., transforming resulting models into APIs).
• Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines feeding these repositories and the ML feature or data stores are working as intended.
• Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.

Technical Skills

• At least 10 years of experience as a ML Engineer, working with Python, ML libraries, and large-scale data processing framework.
• Advance proficiency in Python used both for ML and automation tasks.
• Experience in working with ML libraries such as Panda, NumPy, H2O, or TensorFlow.
• Experience in working with large-scale data processing framework, such as Hadoop, Spark, or Dask.
• Knowledge of OpenShift / Kubernetes is a must-have.
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Knowledge in the operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g., Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, Dataiku, H2O, or DKube).
• Knowledge of Workflow Orchestrator, such as Airflow or Ctrl-M.
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
• Experience in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms.
• Knowledge of cloud platforms (e.g. AWS, GCP) would be an advantage.

We seek individuals with highly developed conceptual, strategic, and analytical skills, capable of striking a balance between visionary thinking and practical solutions. The ability to comprehend, inspire, and mobilize others is crucial. A business-oriented mindset coupled with effective storytelling will drive your success. We are looking for self-starters ready to take on responsibilities with enthusiasm.

• Developing and maintaining the entire DevOps pipelines.
• Coordinate with the stakeholders from requirements gathering until successful implementation DevOps pipeline on boarding.
• Work with the vendors and for internal platforms to setup centralized DevOps solutions considering market best practice, Industry standard and ease of support.
• Work with the vendors and for internal platforms to upgrade the DevOps tools farm and integrating with tools.
• Lead analysis and resolution of root cause for Test Orchestration / Environment related issues
• Ability to multitask and work in a fast-paced, collaborative team environment.
• Stays current with industry trends and leads development of key DevOps, Runtime, and Operational innovation platforms

• Deep technical background, with hands-on experience in supporting CI/CD pipelines (Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA and Confluence).
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Skill to containerize a application and good if Kubernetes
• Good Experience on OpenShift or AWS
• Prior technical background on different build and branching strategies.
• Deep technical background on Kubernetes deployment process.
• Good knowledge on maintaining/deploying secrets in Kubernetes.
• Prior working experience in setting up Jira workflow.
• Strong hands-on experience on Shell or Groovy scripting.
• Prior experience is customizing JIRA and Setting up confluence spaces.
• Prior hand-on experience in setting up CI/CD pipeline as a centralized solution.
• Hand on experience in setting up DevOps governance, Security standards and audit requirements.
• Prior experience in setting up DevOps pipeline in internal and external cloud offerings.
• Experience with continuous testing, techniques and tools (Junit, Sonar Cube, Veracode etc.)
• Technical exposure of automation accomplished with advanced Python, Chef, Ruby and PowerShell
• Working knowledge of Murex, MxTest, Mx pipeline and Machine Learning applications will be an advantage.

Development, Production and User Support, Configuration and Optimisation of the SWIFT AMH Applications. Assist to generate reports using AMH Database and native sql.

Key Responsibilities

Support, coordinate and lead all technical activities regarding solutions delivery for the area – for both business-as-usual and project delivery.

Track and review the performance of the assigned team or developers and business/systems analysts and remediate any issues.

Identify system issues and collaborate with technical support and development teams to drive resolution, provide a complete RCA to the client.

Monitor and review production stability i.e. manage amount of issues, reoccurrence, processes, change control

Facilitate and ensure the upgrade of all software and hardware.

Attain client confidence through demonstrable technology experience.

Participates in disaster recovery/business continuity activities as needed.

Research and evaluate new technologies, products and techniques that could meet future banking needs.

4-6 years as a SWIFT or java Developer

Good experience with Swift AMH tool. Good in creating reports using AMH database.

Has a Good knowledge and application of the SDLC and agile principles.

Has been involved in the development, implementation of at least one major application.

Knowledge of Oracle databases, strong sql, Linux OS, IBM MQ / jms, shell scripting, Oracle DB, open source DB’s, Api’s, Cloud technologies, Agile Methodology

Knowledge and experience with SWIFT, AMH and/or payments systems in the bank.

Good understanding of the system development life cycle

Experience with software development methodologies

Worked in a multi-project environment.

Liaising with vendors

We are seeking a talented and experienced Data Engineer (Quantexa)with expertise in Hadoop, Scala, Spark, Elastic, Open Shift Container Platform (OCP) and DevOps practices. Elasticsearch to join our team. As a Data Engineer, you will play a crucial role in designing, developing, and optimizing big data solutions using Apache Spark, Scala, and Elasticsearch. You will collaborate with cross-functional teams to build scalable and efficient data processing pipelines and search applications. Knowledge and experience in the Compliance / AML domain will be a plus. Working experience with Quantexa tool is a must.

Responsibilities:

·        Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives

·        Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions

·        Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data

·        Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data

·        Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch

·        Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch

·        Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards

·        Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration

·        Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components

·        Ensure data quality and integrity throughout the data processing lifecycle

·        Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques

·        Optimize data engineering workflows for containerized deployment and efficient resource utilization

·        Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability

·        Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance

·        Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements

·        Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure

·        Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference

1. More than 5 years of experience as a Data Engineer
2. · Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline
3. · Possession of Quantexa certification as a Data Engineer or Data Architect, with proficiency in the tool
4. · Demonstrated experience as a Data Engineer, utilizing Hadoop, Spark, and data processing technologies in large-scale environments
5. · Expertise in the Scala programming language and familiarity with functional programming principles
6. · Prior experience with the Quantexa tool is highly desirable
7. · Comprehensive understanding of Apache Spark architecture, including RDDs, DataFrames, and Spark SQL
8. · Advanced proficiency in designing and developing data infrastructure utilizing Hadoop, Spark, and associated tools (HDFS, Hive, Pig, etc.)
9. · Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration via Kubernetes
10. · Proficiency in programming languages commonly employed in data engineering, including Spark, Python, Scala, or Java
11. · Knowledge of DevOps methodologies, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
12. · Experience with Graphana, Prometheus, and Splunk will be considered an added advantage
13. · Background in integrating and utilizing Elasticsearch for data indexing and search applications
14. · Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization techniques
15. · Experience with distributed computing, parallel processing, and handling large datasets
16. · Proficient in performance tuning and optimization methods for Spark applications and Elasticsearch queries
17. · Strong problem-solving and analytical capabilities with the capacity to debug and resolve intricate issues
18. · Familiarity with version control systems (e.g., Git) and collaborative development environments

We are looking for a motivated and innovative Software Engineer with a passion for Machine Learning and Artificial Intelligence. This role is ideal for fresh graduates with a solid foundation in Python programming and an eagerness to work on AI-driven solutions. You will be a part of a collaborative team developing intelligent systems and applications that solve real-world problems.

Key Responsibilities:

• Develop, test, and deploy scalable software applications using Python.
• Collaborate with data scientists and AI researchers to build machine learning models and integrate them into production systems.
• Write efficient code to implement AI algorithms, automating data processes, and deploying AI models.
• Assist in developing machine learning pipelines, data pre-processing, feature extraction, and model training.
• Analyze and optimize machine learning algorithms for performance and scalability.
• Participate in code reviews, design discussions, and system architecture planning.
• Work closely with the product development team to translate requirements into technical solutions.
• Stay up-to-date with the latest trends and advancements in AI and machine learning.

Educational Background: Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.

Programming Skills: Proficiency in Python; experience with libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch is a plus.

Machine Learning Knowledge: Familiarity with machine learning algorithms and frameworks.

AI Experience: Basic understanding of AI concepts and how they are applied to real-world problems.

Database Skills: Experience with SQL and NoSQL databases is an advantage.

Analytical Thinking: Strong problem-solving skills with attention to detail.