Data Engineer

Data Engineer responsible for building and maintaining scalable data pipelines and infrastructure. Ensuring data accuracy and consistency across high-volume transactional and API-driven systems.

Posted 7/18/2026full-timeHammersmith • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining ETL/ELT pipelines, ensuring data accuracy and availability while optimizing performance and cost-efficiency. Proficient in data transformation techniques and integrating various data sources to support analytics.

Highest-signal resume keywords

ETL/ELT Pipeline DesignPython ProgrammingSQL ProficiencyData Transformation TechniquesData Warehousing Concepts

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringBackend EngineeringData Pipeline DesignData OrchestrationWorkflow ToolsData ModellingFault-Tolerant SystemsData ValidationData MonitoringData Accuracy

Soft Skills

Problem-SolvingAttention to Detail

Tools & Technologies

APIsData Processing WorkflowsData Infrastructure

Industry Keywords

Data IngestionEvent SequencingIdempotencyTransactional DataAnalytical Datasets

Tech Stack

Tools & technologies

Distributed SystemsETLPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain ETL/ELT pipelines
Ingest data from internal systems and external APIs
Develop scalable data processing workflows (batch and/or real-time)
Ensure pipelines are reusable, efficient, and maintainable
Integrate data from various sources, including transactional flows
Handle complex data scenarios such as: Event sequencing (e.g. bet → resolve), Idempotency and duplicate handling, Partial or delayed data
Ensure consistency between source systems and analytical datasets
Implement transformation logic aligned with architectural data models
Build and maintain structured data layers for analytics consumption
Collaborate closely with the Data Architect on model implementation
Implement data validation, monitoring, and alerting mechanisms
Identify and resolve data inconsistencies or failures
Ensure high levels of data accuracy and availability
Optimise pipelines for performance and cost-efficiency
Support scaling of data infrastructure as volumes grow
Ensure low-latency data availability where required
Work closely with Data Architect, Analysts, and Manager
Support Analysts by ensuring availability of curated datasets
Contribute to continuous improvement of data platform capabilities

Requirements

What you’ll need

3–7+ years experience in data engineering, backend engineering, or similar roles
Strong programming skills (e.g. Python, SQL)
Solid understanding of ETL/ELT processes and data pipeline design
Experience working with APIs and integrating distributed systems
Experience handling transactional or event-based data
Strong understanding of: Data transformation techniques, Data warehousing concepts, Data modelling fundamentals
Experience with data orchestration and workflow tools
Ability to build robust, fault-tolerant systems
Strong problem-solving skills with attention to detail and data accuracy.

Benefits

Comp & perks

26 days paid holiday per year.
Competitive salary
€400 annual wellness Allowance
Hybrid Working
Risk Benefits such as pension, Life Assurance (4x annual salary), Private Medical Insurance
Team Building Opportunities
Flexible core hours between 10am – 4pm
Receive support whenever you need it with our Employee Assistance Program, available 24/7.
Local discounts and more.