Data Engineer - SQL/Data Quality/ETL/Data Warehousing
- London (5 Days Onsite)
- 12-Month Contract
- Up to £539.57/day Inside IR35
We are looking for an experienced Data Engineer to join a major global financial services organisation on an initial 12-month contract.
This is a hands-on role combining advanced SQL, data engineering, data quality, data lineage and root-cause analysis. You will work across complex enterprise data environments, identifying how data moves between systems, diagnosing quality issues and building sustainable solutions rather than simply fixing symptoms.
The successful candidate will be equally comfortable investigating existing data flows and building robust data solutions, working closely with product, platform and source-system teams.
Key Responsibilities
- Use advanced SQL to interrogate complex datasets, perform reconciliation and translate business questions into reliable, auditable data.
- Conduct data mining and root-cause analysis across multiple internal, product and enterprise data sources.
- Map end-to-end data lineage, covering source, ingestion, transformation and serving layers.
- Identify system ownership, dependencies, interfaces and upstream/downstream data contracts.
- Profile data and design effective data quality controls, rules, thresholds and alerting.
- Investigate data quality failures and deliver durable remediation at the underlying root cause.
- Design and build curated warehouse/domain data layers, scalable data marts and consistent data definitions.
- Develop reliable ETL/ELT pipelines, including incremental processing, backfills and safe reruns.
- Work with concepts including CDC, idempotency and late-arriving data.
- Implement monitoring, reconciliation checks and observability to maintain pipeline and data-product health.
- Establish practical processes for data quality issue intake, prioritisation, remediation, validation and ongoing sustainment.
- Work collaboratively with analytics/product teams, platform engineering teams and source-system owners.
- Produce high-quality documentation including lineage diagrams, data definitions, DQ rule catalogues, process documentation and operational runbooks.
- Lead technical discovery workshops covering systems, data flows and data quality root causes.
Essential Experience
- Strong, hands-on SQL skills including complex querying, joins, window functions, query optimisation and performance tuning.
- Strong commercial Data Engineering experience within complex data environments.
- Proven data quality engineering experience, including profiling, DQ rules, controls, monitoring and root-cause remediation.
- Experience performing complex data analysis, mining, reconciliation and anomaly investigation.
- Strong understanding of data lineage and end-to-end data flows.
- Experience designing and developing ETL/ELT pipelines.
- Data warehouse or domain data platform experience.
- Understanding of dimensional and/or domain-oriented data modelling.
- Experience creating curated data layers and/or scalable data marts.
- Strong troubleshooting skills across data pipelines and platforms.
- Excellent stakeholder management and cross-functional collaboration skills.
- Strong technical documentation skills.
Desirable Experience
- Knowledge of data-platform compute infrastructure, orchestration, storage and compute trade-offs.
- Experience with data governance, ownership models, RACI, stewardship and issue lifecycle management.
- Understanding of data-platform security, access controls, least privilege and auditability.
- Experience working within structured incident, change and problem-management environments.
- Exposure to ITIL-style processes.
- Experience working within large, matrixed enterprise environments.
- Ability to quickly understand existing tools, standards and engineering patterns.
The Opportunity
This role would suit a Data Engineer who enjoys getting underneath complex data problems rather than simply building pipelines from predefined requirements. You will have the opportunity to influence both immediate data-quality remediation and the longer-term development of sustainable data platforms and processes.
You will need to be comfortable operating in a fast-moving enterprise environment, communicating across technical teams and taking ownership of complex data investigations from discovery through to resolution.
Please note: This position requires 5 days per week onsite in London.