Datagaps - ETL Test Architect - Data Warehouse Testing

: 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 modern 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