{"id":3861028,"url":"https://alion.io/job/mastek-data-engineerbi-developer-daa-3","title":"Data Engineer/BI Developer-DA&A","company":{"id":59435,"name":"Mastek","domain":"mastek.com","url":"https://alion.io/company/mastek","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"A","score":88,"open_postings":4,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":28,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitOps","optional":false},{"name":"Helm","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Postman","optional":false},{"name":"PowerShell","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Rest-Assured","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-11-06T09:24:58Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T04:58:48Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Title\nData Engineer / BI Developer - DA&A (Quality Engineering - Data Testing - iCEDQ)\nExpected Work Experience\n3 to 6 Years\nJob Location\nIndia\nJob Summary\nOwn the quality strategy and executable assurance for onboarding self-service data and BI solutions within the DA&A domain. This role validates functional behavior, module contracts, idempotency, parallel execution, approvals, failure diagnostics, resume/recovery, telemetry, security-adjacent controls, performance evidence, and operational readiness across defined data application patterns and multiple environments. Candidate must have relevant experience of 3 to 6 Years.\nKey Responsibilities\nOwn the quality strategy and executable assurance for the onboarding self-service solution for data and BI workloads.\nValidate functional behavior, module contracts, idempotency, parallel execution, approvals, failure diagnostics, resume/recovery, telemetry, security-adjacent controls, performance evidence, and operational readiness across the defined application patterns and eight environments.\nQuality planning and traceability\nCreate the master test strategy, test pyramid, environment approach, entry/exit criteria, defect workflow, evidence standards, and acceptance traceability matrix.\nMap tests to both application patterns, all eight environments, one-time and per-environment modules, orchestration, approvals, dashboard, email, and handover deliverables.\nDefine test data and naming practices that avoid collisions and permit safe cleanup and repeat execution.\nAutomation and functional validation\nAutomate request-schema/default validation, module-level checks, integration tests, and end-to-end onboarding tests.\nValidate repository scaffolding, starter application health check, CI/CD asset generation, Terraform outcomes, Helm releases, GitOps registration, access, and secrets references.\nConfirm that Release Workflow request, trigger, run status, approval evidence, and final outcome are correct and auditable.\nValidate that the five NonProd environments execute in parallel and production environments run only after the required approval.\nResilience, recovery, and non-functional testing\nExecute repeatability and idempotency tests to confirm reruns do not create duplicate or conflicting resources.\nInject controlled failures at module and orchestration steps; verify diagnostics, retained state, retry behavior, resume point, and audit history.\nTest invalid requests, missing access, unavailable dependencies, approval rejection/hold, unstable environments, timeouts, partial provisioning, and GitOps/health-check failures.\nMeasure happy-path elapsed time against the current baseline and report actual results without treating the design target as an SLA.\nValidate that sensitive values do not appear in logs, generated summaries, dashboard content, or test artifacts.\nOperational readiness and acceptance\nValidate dashboard calculations and views for runs, success rate, elapsed time, and failures by step; verify summary-email completeness and accuracy.\nProduce the formal test report covering repeatability, idempotency, failure/recovery, and elapsed-time results.\nReview runbooks and troubleshooting guides by executing recovery procedures; identify gaps before knowledge transfer.\nProvide gate-ready quality evidence, support demonstrations and production launch, and verify warranty defect fixes.\nOther Capabilities\nApply quality engineering practices to data pipelines, BI models, and analytics platforms using iCEDQ or similar data testing tools.\nCollaborate with Data Engineers, BI Developers, platform teams, and SRE/DevOps engineers to design testable data and automation patterns.\nEnsure traceability from data requirements and SOW acceptance criteria through test scenarios, automated checks, evidence, defects, and gate sign-off.\nContribute to continuous improvement of data quality, observability, and operational readiness across DA&A solutions.\nCommunicate complex quality findings clearly to technical and non-technical stakeholders and support production launch decisions.\nQualifications and Skills\nRequired experience and qualifications\n5-8 years in quality engineering, test automation, DevOps/platform testing, SRE validation, or infrastructure automation assurance.\nHands-on experience testing CI/CD pipelines, APIs, infrastructure as code, Kubernetes/AKS deployments, or enterprise workflow integrations.\nStrong automation skills in Python, PowerShell, Bash, or a comparable language, with API and command-line validation experience.\nExperience designing test evidence for milestone acceptance and production-readiness decisions.\nBachelor’s degree in a technical discipline or equivalent practical experience.\nMandatory technical competencies\nTest strategy for distributed automation spanning request forms, APIs, Jenkins orchestration, Terraform, CI/CD assets, Helm, GitOps, secrets, and AKS.\nAutomated API/schema/configuration validation, pipeline test hooks, infrastructure assertions, Kubernetes health checks, and end-to-end verification.\nIdempotency, repeatability, concurrency/parallelism, negative testing, failure injection, retry/resume, partial-state, and recovery testing.\nTelemetry validation covering run IDs, step timings, logs, audit records, dashboard measures, failure classification, and summary-email accuracy.\nDefect isolation across workflow, orchestration, cloud provisioning, pipeline generation, deployment, access, secrets, policy, and environment layers.\nTraceability from SOW acceptance criteria to test scenarios, automated checks, evidence, defects, and gate sign-off.\nPreferred / value-adding experience\nExperience with pytest, Pester, REST-assured/Postman/Newman, Terratest, Helm test, Kubernetes test tooling, or equivalent approaches.\nExperience with chaos/failure-injection techniques in controlled NonProd environments.\nISTQB, Azure, Kubernetes, or DevOps-related certification.\nExperience validating dashboards/telemetry and operational runbooks for platform products.\nRole-specific skills\nExperience in Data Automation & AI within DA&A environments.\nHands-on experience with Quality Engineering - Data Testing using iCEDQ or comparable data testing tools.\nAbility to design and execute data validation, reconciliation, and regression suites for data pipelines and BI solutions.\nUnderstanding of data warehousing, ETL/ELT processes, and BI/reporting workflows from a testing and automation 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