Data Engineer

• Design, maintain, and document data pipelines and products while ensuring data quality and alignment with operational sources
• Oversee database performance, security, and access, while monitoring usage, archiving historical data, and identifying design improvements
• Develop and uphold coding, naming, change control, and extraction/loading standards
• Provide statistical and reporting support to the Business Intelligence team
• Support data lakehouse operations, delivering key projects, including data migrations, on time
• Partner with IT and business teams to manage relationships and ensure effective service delivery
• Actively manage personal learning, development, and growth while contributing to complex problem-solving

Senior Data Engineer

• Designs, builds, and maintains complex data processing systems
• Ensures data integrity and optimizes pipelines for efficiency and scalability
• Troubleshoots complex data issues and conducts quality checks
• Mentors junior team members and fosters collective growth
• Maintains clear documentation for data solutions
• Identifies optimization opportunities and plans implementation
• Delivers new solutions or expands existing solutions based on received briefs
• Takes responsibility for security in PII data, code management, and deployment
• Proactively identifies improvements for dashboards across the business
• Engages with projects, providing support in modeling feasibility and blockers
• Conducts quality checks and ensures technical implementations meet standards
• Independently owns small-scale projects and delivers them by meeting success criteria and deadlines.

Freelance Data Engineer

• Manage an assigned team through day-to-day support tasks
• Oversee development plans for the team and provide mentorship to the team
• Provide guidance and peer review
• Support pipelines end to end
• Build and deploy enhancements and new developments or new data pipelines
• Identify and drive optimisation opportunities across the environment
• Manage the handover of new applications ensuring that required standards and practices are met
• Improvement on recovery time in case of prod failures
• Test prototypes and oversee handover to the Data Operations teams
• Attend and contribute to regular team and User meetings
• Responsible for the actual coding or programming of Hadoop applications
• High-speed querying

Specialist Support Engineer – DataOps

• Design, build, and maintain scalable and secure ETL/ELT pipelines across Redshift, S3
• Develop and manage AWS Glue jobs for automation, transformation, and catalog management
• Implement Apache Airflow workflows for data orchestration and monitoring of cross-market processes
• Integrate data from external partners (MNOs, financial institutions, third-party APIs) into the centralized warehouse
• Monitor and remediate infrastructure vulnerabilities in collaboration with the security team
• Work with analysts and data scientists to prepare structured datasets for reporting, modeling, and insights

• Design, implement, and maintain scalable data warehouse architectures (Star/Snowflake) and optimize ETL/ELT pipelines for data quality.
• Write and tune complex SQL (T-SQL/ANSI) and use Python for data manipulation and advanced analytics.
• Own the full SDLC: requirements, design, testing, deployment, and solution estimation.
• Collaborate with stakeholders to translate business data needs into technical structures.
• Identify and resolve performance bottlenecks through normalisation, indexing, and query optimization.
• Develop and maintain dashboards/reports using tools like Power BI or Yellowfin for data-led decision-making.
• Create and maintain high-quality technical documentation (data flow diagrams, specifications, metadata).
• Actively participate in the Agile/Scrum framework and sprint ceremonies.
• Research and evaluate emerging data technologies to continuously improve the data warehouse.

Data Warehouse Engineer

• Lead, hire, and develop a team of data engineers, including performance management and career growth
• Own end-to-end delivery, including sprint planning, prioritization, and execution
• Establish engineering standards and ensure high-quality, consistent output
• Partner with cross-functional stakeholders to align data initiatives with business priorities
• Design and evolve scalable data architecture across ingestion, transformation, storage, and consumption layers
• Build and maintain high-volume ETL/ELT pipelines for real-time and batch data
• Lead data modeling, governance, and data quality practices
• Drive adoption of AI and automation across data engineering workflows
• Partner with data science teams to operationalize models and embed AI into data products
• Evaluate and implement emerging tools with a focus on practical impact

Lead Data Engineer

• Design, build, and maintain robust, scalable data pipelines and ETL/ELT workflows
• Develop and manage data warehousing solutions to support business intelligence and analytics needs
• Ensure data quality, integrity, and availability across all data systems and sources
• Collaborate with data scientists, analysts, and product teams to understand and fulfill data requirements
• Optimize query performance and database architecture for speed and efficiency
• Monitor, troubleshoot, and resolve data pipeline failures and incidents
• Implement and enforce data governance, security, and compliance best practices
• Document data models, processes, and infrastructure to support team knowledge sharing

• Design and implement pipelines that ingest payment events into analytics infrastructure
• Build well-structured dbt models for downstream use
• Work with streaming data via Confluent and Hevo into Snowflake
• Instrument pipelines with monitoring and alerting
• Operate and improve core stack — Snowflake, Confluent, Hevo, dbt, Lightdash
• Manage schema evolution as upstream systems change
• Build data quality checks ensuring analytics-layer data reconciles with source systems
• Maintain clear documentation of models and architecture

• Contributing as part of a SCRUM/KANBAN squad team to develop cutting-edge legal AI solutions.
• Ensuring technical consistency and overall code quality and maintainability, co-create technical components with the architects of the products.
• Defining, coordinating and providing direct input to project plans.
• Writing and reviewing portions of detailed specifications for the development of complex AI agents system components.
• Implementing development processes, coding best practices and code reviews, resolve technical issues as necessary.
• Keeping abreast of new technology developments and follow global RELX technical strategy.
• Mentoring more junior members of the team.

Data Engineer III

• Design, build, and maintain scalable, efficient, and reliable data pipelines using Ab Initio
• Develop robust ETL (Extract, Transform, Load) processes to handle large volumes of data
• Integrate structured and unstructured data from multiple sources
• Monitor the performance of data pipelines and ETL workflows
• Act as a liaison between data scientists and business analysts
• Proactively identify, troubleshoot, and resolve data-related issues

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