Job Title

Job Role - QA with Azure and Databricks Experience Required - 7 to 14 Years Location - Indore/ Pune/ Chennai/ BangaloreImmediate joiners are preferred.Key Responsibilities 1) Test Strategy & Planning Define and maintaintest strategiesfor data pipelines, notebooks, jobs, and APIs across Databricks & Azure. Translatebusiness rulesanddata quality SLAsinto testable acceptance criteria. Establishrisk-basedtest plans across functional, integration, system, andnon-functional(performance, scalability, security) testing. 2) Data & Pipeline Testing (Databricks / Spark / Delta) Developautomated testsforSparktransformations (e.g.,PySpark ,Spark SQL ) andDelta Lakefeatures (MERGE, time travel, schema evolution). Implementdata quality checks(completeness, accuracy, consistency, referential integrity, drift detection). Validatebatch and streamingpipelines, job dependencies, and SLAs. Createreproducible test datasetsand useDelta Live Tables(if applicable) to validate expectations. 3) Azure Cloud QA Test data flows acrossAzure Data Factory / Synapse pipelines , Databricks Jobs,Azure Storage/ADLS ,Azure SQL/SQL MI ,Event Hub/Kafka , andKey Vaultaccess patterns. VerifyIAM/ACLs/Unity Catalogpermissions, secrets handling, andnetwork boundarycontrols. Validateinfrastructure configurationsacross environments (Dev/Test/Prod) and supportIaCvalidation (e.g., Bicep/Terraform plan diffs). 4) Automation & DevOps Integrate tests intoCI/CD(Azure DevOps/GitHub Actions): unit, integration, data-validation, andpost-deploymentsmoke tests. Implementquality gates(coverage thresholds, schema checks, contract tests, static checks like Pylint/flake8). Buildtest utilitiesand shared libraries for data assertions, fixtures, and synthetic data generation. Usefeature branches , PR checks, andmerge policiesto enforce quality. 5) Observability & Reliability Instrument tests and pipelines withlogging & metrics(e.g., Azure Monitor, Log Analytics, Databricks metrics). DefineSLIs/SLOsfor data quality andpipeline reliability ; participate in incident reviews and RCA. Establishquality dashboards(test pass rate, DQ incidents, recovery time, flaky test rate). 6) Collaboration & Governance Partner withdata engineers, platform engineers, product owners, and data stewards . Contribute totest data managementpractices and adata contractapproach with upstream/downstream teams. Document test plans, runbooks, andtraceabilityfrom requirements to tests.Required Qualifications 3–8+ yearsin QA/Test Engineering with2+ yearsindata platformorSpark-basedenvironments. Hands-on withDatabricks : Notebooks, Jobs, Delta Lake, cluster policies. StrongPythonfor tests/utilities; solidSQLfor validation and profiling. Experience testingETL/ELTpatterns, data partitioning, late-arriving data, slowly changing dimensions, idempotency. Azureexperience:Data Factory ,ADLS Gen2 ,Key Vault ,Azure DevOps/GitHub . CI/CD for data: pipelines, artifacts, environments, approvals,test stagesandpost-deployvalidations. Familiar withschema validationandAPI testing(REST/Databricks Jobs API). Clear understanding ofsecurity(RBAC/ABAC, managed identities),cost & performanceconsiderations.Nice-to-Have Unity Catalog , data lineage, and governance testing. Streaming(Structured Streaming, Delta Live Tables),event-drivenvalidation. Performance testingof Spark jobs (cluster sizing, shuffle hotspots, skew). Exposure toprivacy®ulatorycontrols (PII masking, GDPR/CCPA, SOX).About InfoBeans: InfoBeans is a global digital transformation and product engineering company, enabling businesses to thrive through innovation, agility, and cutting-edge technology solutions. With over 1,700 team members across the globe, we specialize incustom software development, enterprise solutions, cloud, AI/ML, UX, automation, and digital transformation services .At InfoBeans, we live by our core purpose of“Creating WOW!” —for our clients, team members, and the community. Our collaborative culture, growth opportunities, and people-first approach make us one of the most trusted and rewarding workplaces.