Data SDET / Lead Data Quality Engineer

Altrapoint; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Altrapoint is seeking a Data SDET / Lead Data Quality Engineer for London with a hybrid work arrangement. The role focuses on testing data pipelines in a buy-side financial context, validating Azure Databricks lakehouse transformations and ensuring data quality across Bronze-Silver-Gold layers.

The successful candidate will own test strategy, collaborate with Data Engineers and Cloud Architects, and drive QA in migration of legacy data to cloud platforms. Permanent or FTC opportunities available.

Qualifications

• Experience testing data pipelines in buy-side Asset Management, Wealth Management, or capital markets.
• Hands-on experience validating cloud data pipelines on Azure Databricks, PySpark, Spark SQL, Delta Lake and Azure Data Factory.
• Proven experience testing Medallion architectures and automated source-to-target ETL/ELT transformations.
• Confident, self-directed Technical Tester / QA Lead in Agile delivery setups.

Responsibilities

• Take ownership of data pipeline quality engineering.
• Design, build, and execute automated test frameworks across cloud data platforms.
• Validate multi-layered Lakehouse data flows (Bronze, Silver, Gold).
• Perform source-to-target mapping & reconciliation across IBOR, holdings, transactions, and market data feed ingestions.

Skills

Data QA

Data Engineering testing

Azure Databricks

PySpark

Spark SQL

Delta Lake

Azure Data Factory

Agile delivery

Lead QA

Tools

Azure Databricks

PySpark

Spark SQL

Delta Lake

Azure Data Factory

Job description

Data SDET / Lead Data Quality Engineer | Management Consulting | Asset Management | London (Hybrid)

Buy‑side Asset Management or Wealth Management domain experience required

London Hybrid (3 days per week at City of London office, Bank / Cheapside area).

A fast-growing boutique financial services management consultancy is partnering with a major global asset management platform undergoing a multi-year middle-office transformation. As part of building out a centralised cloud Data Lakehouse (IBOR data spine: holdings, transactions, securities, and pricing), they are seeking high‑calibre Data SDETs and Lead Data QA Engineers to validate modern cloud data pipelines from end to end.

This is a Permanent or Fixed-Term Contract (FTC) opportunity designed for long-term career growth within a specialist digital delivery practice.

As the successful candidate, you will:

Take ownership of data pipeline quality engineering: Design, build, and execute automated test frameworks across cloud data platforms (Azure Databricks, Delta Lake, Azure Data Factory).

Validate multi-layered Lakehouse data flows: Test transformations across Bronze, Silver, and Gold Medallion layers, ensuring business logic, data reconciliation, schema validation, and SCD Type 2 handling remain rock‑solid.

Perform source-to-target mapping & reconciliation: Validate data integrity across complex financial datasets, including investment book of record (IBOR), portfolio holdings, transactions, and upstream market data feed ingestions.

Act as a technical quality gate: Partner directly with Data Engineers, Cloud Architects, and Business Stakeholders to review technical proposals, manage test releases, and validate legacy platform migrations to the cloud.

Candidate Requirements

Required

• Strong background in Data QA / Data Engineering testing within buy-side Asset Management, Wealth Management, or Capital Markets environments.
• Hands‑on expertise validating cloud data pipelines built on Azure Databricks, PySpark, Spark SQL, Delta Lake, and Azure Data Factory.
• Proven experience testing Medallion architectures and automated source‑to‑target ETL/ELT transformations using Python or SQL.
• Confidence operating as a self‑directed Technical Tester / QA Lead in Agile delivery setups.
• Comfortable committing to 3 days/week onsite in the City of London (Bank / Moorgate area).
• Open to Permanent or Fixed‑Term Contract (FTC) engagement models.

Nice to Have / Ideal

• Experience with legacy DWH/ETL migrations (e.g., SAP BODS, SSMS, or mainframe to Databricks Lakehouse).

This is an exceptional opportunity to join a high‑growth consultancy delivering high‑impact cloud data initiatives across major global financial institutions.