We are looking for a Software Development Engineer in Test (SDET) to design, build, and maintain automation-first test frameworks for data validation and regression testing across capital markets data pipelines spanning legacy and modern platforms. This is a hands-on engineering role focused on building scalable, reusable test automation solutions (Python/PySpark/SQL) that validate data accuracy, completeness, consistency, integrity, and business-rule conformance across post-trade and enterprise data ecosystems. Please share an updated profile to [email protected]

(+91)74839 25904

Mode of Work:Hybrid

Job Location:Gurugram,Pune,Bangalore Key Responsibilities

Test Automation & Framework Development.

- Design, build, and maintain automation-first regression testing frameworks using Python, PySpark, and SQL.
- Develop reusable validation utilities, libraries, APIs, and CLI tools to support data validation, orchestration, and reporting workflows.
- Architect scalable test frameworks supporting batch and cloud-based execution models.
- Build field-level, dataset-level, transformation-level, and aggregate-level automated data checks across source, staging, warehouse, data lake, and downstream systems.

Data Validation

Engineering

- Perform source-to-target data validation across legacy and modern systems, including SQL Server and cloud-based environments.
- Automate validation of data accuracy, completeness, consistency, timeliness, duplication handling, referential integrity, schema structures, metadata, and lineage.
- Validate ETL/ELT pipelines, post-trade data flows, stored procedures, batch jobs, and cloud-based execution workflows.
- Write, optimize, and troubleshoot complex SQL queries and stored procedures across SQL Server, Oracle, PostgreSQL, or similar platforms.
- Translate business rules, stored procedure logic, and post-trade process flows into automated validation scripts and assertions. CI/CD & Pipeline Integration




- Integrate regression tests, data validation checks, SQL deployables, and quality gates into CI/CD pipelines using Azure DevOps, Jenkins, GitLab, or equivalent tools.
- Automate execution of AutoSys jobs, batch processes, stored procedures, and validation scripts across dev, UAT, and production environments.
- Work with engineering teams to embed data quality controls into pipelines, releases, and operational workflows.

Quality

Engineering & Defect Analysis

- Design reusable test cases, validation scenarios, reconciliation checks, and regression packs for repeatable data-quality assurance.
- Identify data anomalies, schema mismatches, duplicate records, null-handling issues, transformation failures, reconciliation breaks, and integrity violations.
- Log defects with clear evidence, impact analysis, root-cause observations, and business context.
- Support capital markets and post-trade validation across allocations, clearing, settlement, confirmations, reconciliations, market data, reference data, and downstream reporting. Collaboration
- Partner with engineering, business, and product teams to define requirements, resolve issues, and ensure test coverage.
- Contribute to test strategy, quality standards, and best practices as part of an Agile delivery team.
- Communicate test status, risks, and quality metrics clearly to technical stakeholders. Key Competencies / Requirements
- 8–10 years of hands-on experience as an SDET, Test Automation Engineer, or Data Engineer in QA, with a strong software engineering background.




- Strong Python skills for building automation frameworks, validation utilities, and regression test suites (not just running scripts, but designing maintainable, reusable code).
- Working knowledge of PySpark for validating large-scale, distributed data pipelines.
- Solid SQL skills for source-to-target validation, reconciliation, complex queries, stored procedures, and schema checks.
- Practical experience with ETL/ELT testing, data pipeline testing, and regression automation across legacy and modern platforms.
- Solid understanding of data quality dimensions: accuracy, completeness, consistency, timeliness, uniqueness, referential integrity, and business-rule conformance.
- Experience validating metadata, schema structures, data types, constraints, lineage, transformation logic, and downstream outputs.
- Hands-on experience with CI/CD tools such as Azure DevOps, Jenkins, or GitLab, and integrating automated tests/quality gates into deployment pipelines.
- Familiarity with batch orchestration tools such as AutoSys, Control-M, or Airflow.
- Experience with JIRA, XRay, and Agile delivery practices.
- Proficiency in leveraging AI-assisted tools such as Claude or GitHub Copilot to accelerate test case generation, SQL development, data validation, defect analysis, documentation, and test data creation.
- Strong analytical skills to understand post-trade, financial, market data, or reference data and translate them into repeatable automated validation.
- Strong communication, problem-solving, and attention to detail. Nice to Have
- Exposure to Azure, AWS, ADF, containers, Kubernetes, or cloud-based data platforms.
- Experience with relational and NoSQL databases such as SQL Server, MongoDB, Cassandra, DynamoDB, or similar.
- Exposure to Hadoop, Spark, Databricks, cloud data lakes, and Big Data validation.
- Experience validating batch, streaming, real-time, and Kafka-based ingestion pipelines.

📌 Software Development Engineer in Test (SDET) (Bengaluru)
🏢 Simpliigence
📍 Bengaluru