{"id":3326192,"url":"https://alion.io/job/morningstar-qa-automation-engineer-data","title":"QA Automation Engineer (Data)","company":{"id":12394,"name":"Morningstar","domain":"morningstar.com","url":"https://alion.io/company/morningstar","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":90,"open_postings":10,"ghost_share":0,"stale_share":0.4,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-10-29T05:49:05Z"}},"role":"QA","role_family":"QA","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"ChatGPT","optional":false},{"name":"Copilot","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-27T10:10:26Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-29T04:09:15Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"The Area: The Investment Management group is a global team guided by Morningstar’s investment principles focused on delivering great long-term investment results to help end-investors reach their financial goals. We use our expertisein asset allocation, investment selectionand portfolio construction to create world-class investment strategies leveragingthe full resources of Morningstar. The group specializes in multi-asset investing, using building blocks in equities, fixed incomeand alternative investments to construct robust portfolios. Through our investment offerings, we serve financial advisers and institutions, and the investors that they serve.\nShift: UK Shift\nRole Summary:\nThe Data Quality Automation Engineerwill join the Systematic Strategies team in the Research & Investment group. This experiencedprofessionalwill design and implement automated data quality controls, validation frameworks, reconciliation processes,and monitoringsolutions across enterprise-scale data platforms.The ideal candidate combines expertisefinancial data managementand automation engineering, with a passion for building scalable controls that improve data qualityand operational efficiency.\nKey Responsibilities\nThe successful candidate will\nDesign, build, and maintainenterprise-scale automated data quality frameworkslikeGreat Expectations, AWS Glue Data Quality, Amazon Deequ, or similar data validation frameworks\n\nExperience implementing and maintainingdata quality controlsby establishingquality metricsfor multi-asset class financial datasets.\n\nDevelop automated monitoring controls capable of identifyinganomalies, outliers, missing data, stale data, and reconciliation breaks\n\nValidate investment datasets sourced from multiple external providers including Bloomberg, FactSet, Morningstar, LSEG, and other market data vendors\n\nDevelop automated source-to-target reconciliation frameworks across ingestion, transformation, and reporting layers\n\nCollaborate with Data Engineering teams to embed data quality controls throughout ETL/ELT pipelines\n\nSupport onboarding and robustness checks for new datasets including validation of data completeness, accuracy, consistency, and fitness for downstream investment and research workflows\n\nRequirements:\nAdvanced Python development\n\nStrong SQL and data analysis skills\n\nHands-on experience with PySparkand distributed data processing\n\nExperience building automated data validation and reconciliation frameworks\n\nExperience working with large-scale structured and semi-structureddatasetsin financial domain\n\nData profiling, anomaly detection, and root-cause analysis experience\n\nRequired Technical Skills\nAdvanced SQL, Python, and PySparkskills\n\nExposure todesigning, developing, and maintainingautomated data quality frameworks\n\nStrong expertisein financial data testing, data profilingand root cause analysis\n\nExposure to cloud-based data platforms and services (AWS preferred)\n\nExposure to AI productivity tools such as ChatGPT, Microsoft Copilot, and GitHub Copilot, with responsible validation ofAI-generated outputs.\n\nPreferred Qualifications\nBachelor's or master'sdegree in quantitative, financial, economic, or engineering discipline\n\n2+ years of experience in Data Quality Engineering, Data Engineering, Analytics Engineering, Financial Data Management, or Investment Technology\n\nMorningstar is an equal opportunity employer.\nMorningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.\nI10_MstarIndiaPvtLtd Morningstar India Private Ltd. 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