:

ETL Test Architect Data Validation, BI Validation & DataOps Suite

Datagaps is looking for a hands-on ETL Test Architect to guide the evolution of DataOps Suite for real-world ETL/ELT validation, BI report validation, data quality, observability, catalog, and test data management use cases.

Role Purpose :

This role requires a senior practitioner who has hands-on experience in complex ETL/ELT, migration, modernization, and BI validation projects and can translate practical validation challenges into product requirements, reusable accelerators, and customer-ready solution patterns.

Key Responsibilities :

- Architect end-to-end validation strategies for ETL/ELT, data warehouse, data lake, cloud migration, modernization, and BI analytics programs.
- Identify corner cases, failure patterns, and validation gaps across pipelines, sources, targets, semantic layers, dashboards, and production data flows.
- Define validation patterns for source-to-target comparison, transformation logic, reconciliation, metadata, schema drift, data quality, observability, and BI report accuracy.
- Provide product guidance for modern platforms such as Databricks, Snowflake, Microsoft Fabric, Azure Synapse, BigQuery, Redshift, and similar ecosystems.
- Work with product, engineering, QA, solution engineering, sales, customer success, and implementation teams to convert field problems into scalable DataOps Suite capabilities.
- Create validation playbooks, reusable templates, solution accelerators, demo scenarios, and customer-facing best practices.
- Support discovery sessions, POCs, solution design workshops, RFP responses, demos, and implementation reviews.

Required Experience and Expertise:

- 10 years of hands-on experience in ETL/ELT testing, data warehouse testing, data migration testing, BI validation, or enterprise data validation programs.




- Strong experience with complex migration and modernization projects across legacy systems, cloud data warehouses, data lakes, lakehouses, modern analytics platforms, and BI platforms.
- Deep understanding of source-to-target testing, transformation validation, reconciliation, aggregation checks, duplicate/null checks, control totals, data completeness, data consistency, and regression testing.
- Practical BI validation experience including report-to-database validation, dashboard regression, visual validation, filter/slicer validation, security validation, performance validation, and BI migration testing.
- Strong knowledge of source- and target-specific validation challenges across databases, files, APIs, cloud storage, SaaS/ERP/CRM systems, streaming feeds, and semi-structured data formats such as JSON, XML, and Parquet.
- Hands-on validation experience with contemporary platforms such as Databricks, Snowflake, Microsoft Fabric, Azure Synapse, BigQuery, Redshift, or similar ecosystems.
- Ability to design validations for CDC, incremental loads, SCD Type 1/2, late-arriving data, deletes, reprocessing, restartability, schema drift, data freshness, SLAs, and production reconciliation.
- Strong communication skills with data engineers, QA teams, BI developers, business analysts, data stewards, architects, customers, and product/engineering teams.

Preferred Qualifications:

- Experience creating reusable validation frameworks, rule libraries, reconciliation patterns, and automation accelerators.
- Exposure to data quality, observability, catalog, lineage, governance,



metadata management, and test data management platforms.
- Experience with Databricks Delta Lake, Snowflake ingestion/streams/tasks, Microsoft Fabric Lakehouse/Warehouse, OneLake, Dataflows Gen2, semantic models, and Power BI validation.
- Understanding of CI/CD integration for data validation using Azure DevOps, Jenkins, GitHub Actions, APIs, or command-line execution.
- Product mindset with the ability to convert practitioner pain points into clear product requirements and scalable platform capabilities.
- Experience supporting pre-sales, POCs, demos, RFPs, customer workshops, or technical enablement for enterprise data testing solutions.

What Success Looks Like:

- DataOps Suite is better aligned with the expectations of ETL testers, BI validation users, data quality teams, observability teams, and test data management users.
- Datagaps gains a credible practitioner voice to identify product gaps, challenge assumptions, and guide roadmap decisions.
- Product, engineering, pre-sales, and implementation teams receive practical validation patterns, platform playbooks, and reusable accelerators.

Ideal Candidate Profile:

The ideal candidate is a senior hands-on data testing architect who has solved complex ETL/ELT, BI validation, migration, modernization, and cloud data platform validation challenges. They should be able to think like a practitioner, architect like a solution owner, and guide Datagaps product teams with real-world validation expertise.

Role Details:

- Role: Software Development - Other
- Industry Type: IT Services & Consulting
- Department: Engineering - Software & QA
- Employment Type: Full Time, Permanent
- Role Category: Software Development

Education:

- UG: Any Graduate

Key Skills:

- Datawarehouse, Databricks, ETL, Snowflake, Reconciliation, Data Validation

📌 Datagaps - ETL Test Architect - Data Warehouse Testing (India)
🏢 Datagaps
📍 India