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Data & Analytics

Senior Data Engineer

Design and build dependable data pipelines and analytical platforms for enterprise transformation programmes across multiple industry contexts.

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LocationLondon, UK

Working styleHybrid / client-aligned

Employment typeFull-time

Experience5–8 years

Technology environment

PythonSQLPySparkAzure Data FactoryDatabricksMicrosoft FabricdbtGit

Industry context

Banking & FinanceAutomotiveMediaEducation

Job description

The Senior Data Engineer will design, implement and operate data pipelines, transformation layers and analytical data products used by client delivery teams and business stakeholders.

The role requires strong engineering judgement around data quality, lineage, performance, security, orchestration and operational support rather than pipeline development in isolation.

Key responsibilities

Design batch and streaming ingestion patterns, transformation pipelines and reusable data components.
Build and maintain data models, validation controls, orchestration, monitoring and failure-recovery patterns.
Work with architects, analysts, application teams and client stakeholders to define data contracts and ownership boundaries.
Review code, deployment pipelines and data-quality evidence before production release.
Support production diagnosis and continuous improvement of data-platform reliability and cost.

Qualifications

5–8 years of professional data-engineering or closely related software-engineering experience.
Strong SQL and Python skills with hands-on experience building production ETL/ELT pipelines.
Experience with Spark/PySpark and at least one modern cloud data platform.
Working knowledge of data modelling, data quality, orchestration, version control and CI/CD.
Ability to explain technical trade-offs clearly to engineering and non-engineering stakeholders.

Preferred qualifications

Experience with Azure Data Factory, Databricks, Microsoft Fabric, dbt or equivalent platforms.
Experience in regulated, high-volume or multi-system enterprise environments.
Knowledge of data lineage, observability, governance and secure data-access patterns.

Benefits & employment terms

Compensation, leave, pension and any role-specific benefits are confirmed during the recruitment process and stated in the written offer.
Any client-site, travel, security-screening or right-to-work requirements are confirmed before appointment.

Nature of working style

Work is organised around project outcomes, engineering standards, peer review and client delivery commitments.
Hybrid attendance and client-site presence vary by engagement and are confirmed for the assigned project.
Engineers are expected to document decisions, communicate delivery risk early and participate in technical review.

Location

Primary employment location is London. Some engagements may require travel to a UK client location; the requirement will be confirmed before assignment.

Working at RC

Delivery standards shape the employee experience

Technology roles are organised around accountable delivery, professional engineering practices and clear client or project outcomes.

Client-impact work

Roles are connected to defined business or delivery outcomes rather than artificial internal assignments.

Professional craft

Engineering, consulting and delivery decisions are expected to be explainable, maintainable and grounded in the operating context.

Clear ownership

Responsibilities, interfaces, quality expectations and escalation paths should be visible across teams and engagements.

Continuous learning

Capability grows through real delivery, peer review, feedback and exposure to changing technologies and business environments.

Hiring journey

A structured process from application to decision

The exact interview sequence may vary by role, but candidates should understand the purpose of each stage and the position they are being assessed for.

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Decision

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