About the role
Job Description
Role: Data Tester — ETL & Data Quality
Location: Bangalore
Level 5
Who are we looking for?
This role sits within the integrated data support team taking over day-to-day operations of the Client data estate the legacy data warehouse, the current Global Data Store (GDS) and the new Databricks-based GDS being built. The tester makes sure every fix, enhancement and release is proven safe before it reaches production, and that data stays complete, accurate and consistent from source systems through to Power BI reports.
Coverage window: 08:00–17:00 UK business hours, Monday–Friday, with support for release and month-end testing as required.
Work Exp – 4+ years in data / ETL testing; hands-on SQL and exposure to ADF and Databricks Technical Skills
Data Tester (ETL & Data Quality)
Attribute
Detail
Role title
Data Tester — ETL & Data Quality
Positions
1 (offshore)
Location
Offshore
Experience
4+ years in data / ETL testing; hands-on SQL and exposure to ADF and Databricks
Reports to
Senior Data Engineer / Data Lead
Role summary
A hands-on Data Tester to validate and protect the quality of data flowing through the Client data estate. The role tests data pipelines at every stage — from source systems into the data lake, through transformation into the warehouse and data marts, and out to reports — and turns repeatable checks into automated regression tests. The successful candidate works closely with the data engineers so that incident fixes, minor enhancements and releases go live without breaking downstream reporting.
Core skills (must have)
Data testing & platform
- ETL / data pipeline testing — validating data between stages using the mapping and business rules of each pipeline.
- SQL — advanced queries to compare, reconcile and profile data across Azure SQL / SQL Server and Databricks.
- Databricks & ADF — understanding of pipelines, notebooks and Delta tables well enough to test them end to end.
- Test automation — building automated regression suites using Python or an ETL testing framework.
- Report testing — validating Power BI and SSRS outputs against source and warehouse data.
Testing types covered
- Data completeness, volume and accuracy testing.
- Data consistency, type, range and relationship testing.
- Data transformation, enrichment and business-rule testing.
- Regression, smoke and release testing across all pipeline stages.
Key responsibilities
- Design, run and maintain test cases for incident fixes, service requests and minor enhancements before they reach production.
- Test data across each pipeline stage — source, data lake, transformation, warehouse, data marts and reports.
- Build and grow an automated regression pack so repeat testing is fast and reliable.
- Run reconciliation checks between source systems and the warehouse, and report exceptions clearly.
- Carry out smoke testing after deployments and overnight batch runs.
- Log, track and retest defects; support root cause analysis with the data engineers.
- Work with data quality tools (DQPro, Ataccama) to strengthen data quality rules and monitoring.
- Maintain test documentation, test data and evidence for release sign-off.
Business & behavioral skills
- Attention to detail — spots small data differences before users do.
- Business understanding — can test against what the data means for underwriting, claims and finance, not just row counts.
- Clear communication — reports defects and test results in plain language with business impact.
- Collaboration — works closely with engineers in an onshore/offshore support model.
Nice to have
- ISTQB or equivalent testing certification; Databricks or Azure fundamentals.
- Experience with ETL test automation frameworks or data comparison utilities.
- Exposure to data quality tooling (DQPro, Ataccama) and insurance or financial services data.
Team roles at a glance
Dimension
Senior Data Engineer
Data Engineer
Data Tester
Positions
1 (lead / onsite)
3 (offshore)
1 (offshore)
Experience
8+ years; 3+ yrs Databricks
4+ years hands-on
4+ years data / ETL testing
Primary focus
L3 escalation & leadership
L2/L3 hands-on support
Data validation & test automation
RCA
Leads & signs off
Performs & documents
Supports with test evidence
Enhancements
Owns design & optimisation
Delivers under guidance
Tests & signs off before release
Stakeholders
Client-facing / governance
Team-facing
Team-facing
Common technology across all roles: ADF · Databricks · Python · SQL · Azure Cloud · Data Quality · Incident Management · Root Cause Analysis · SLA Management.