{"id":1398335,"url":"https://alion.io/job/csc-senior-data-engineer","title":"Senior Data Engineer","company":{"id":20296,"name":"CSC","domain":"cscglobal.com","url":"https://alion.io/company/csc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":89,"open_postings":31,"ghost_share":0,"stale_share":0.419,"repost_share":0.032,"time_to_fill_p50_days":59,"computed_at":"2026-10-04T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":37000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":51},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"LLMOps","optional":false},{"name":"RAG","optional":false}],"status":"closed","first_seen_at":"2026-08-04T12:44:58Z","employer_posted_date":"2026-08-04","last_verified_at":"2026-10-01T12:09:52Z","board_verified":false,"closed_at":"2026-10-01T12:09:52Z","days_open":57,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":57},"description":"Title: Expert Data Engineer\nShift: 11:00AM - 8:00PM\nWork Mode: Hybrid\nLocation: Bangalore\nAI Data Engineering Lead\nIntroduction to the Job:\nThe AI Data Engineering Lead owns the design, build, governance, and operational readiness of the pipelines, data products, and retrieval-ready knowledge assets that power AI-enabled products - ensuring AI is built on trusted, permissioned, explainable, and reusable data rather than fragmented or ungoverned sources. The role partners across product, architecture, AI engineering, platform, security, risk, compliance, and MLOps/LLMOps.\nSome of the things you’ll be doing\nOwn AI-ready data engineering - translate AI product needs into data pipelines and data products for RAG, agents, analytics, and decision support; ensure data is complete, accurate, timely, traceable, and reusable across products and business units; engineer for scale, security, and cost efficiency.\n\nBuild trusted data products - define governed data products across client, entity, product, transaction, finance, risk, vendor, and reference domains, with clear ownership, SLAs, quality expectations, and refresh rules; reduce reliance on spreadsheets and duplicate extracts; partner with data stewards on quality and ownership issues.\n\nEngineer data for RAG and knowledge-based AI - prepare policies, contracts, regulatory content, and operational knowledge for retrieval; define ingestion, chunking, embedding, indexing, and retirement processes; design vector stores, ranking, and grounding/citation patterns with AI engineering; ensure sources are approved, current, and access-controlled.\n\nOwn data quality and trust controls - define and monitor quality rules (completeness, accuracy, validity, timeliness) for critical data elements; build automated checks and remediation workflows into pipelines; ensure AI products can detect missing, stale, or conflicting data; provide quality evidence for risk and product acceptance.\n\nManage metadata, catalog, and lineage - capture business and technical metadata for datasets, pipelines, and vector indexes; ensure assets are cataloged and discoverable; document lineage from source through transformation, embedding, and output for auditability; partner with governance on definitions and ownership.\n\nEmbed access, privacy, and security controls - implement role-, attribute-, jurisdiction-, and purpose-based access so AI products only use authorized data; prevent sensitive data exposure through prompts, logs, embeddings, or outputs; meet minimization, retention, masking, and audit-logging requirements; support security/privacy reviews.\n\nSupport AI data lifecycle operations - monitor pipeline reliability, latency, freshness, and cost; refresh and version datasets, embeddings, and indexes on appropriate schedules; support rollback; partner with MLOps/LLMOps on evaluation and grounding datasets; drive continuous improvement from feedback and production monitoring.\n\nWhat technical skills, experience, and qualifications do you need?\nData engineering: pipeline engineering and orchestration (ETL/ELT, API/event-driven integration); data product development and modeling; data quality rule design and monitoring; metadata, cataloging, and lineage; master/reference data awareness; access control and sensitive data handling; cloud data platforms and lakehouse/warehouse patterns. Any prior experience with StarBurst will be an added advantage.\nAI data: RAG data preparation and document/knowledge ingestion; chunking, embeddings, vector stores, and semantic retrieval; grounding and evaluation datasets; dataset versioning; data prep for AI agents/copilots; freshness, retrieval quality, and source governance; AI data observability; permission-aware retrieval; prevention of sensitive data leakage.\nBusiness and leadership: translating business/product needs into data requirements; strong grasp of data ownership and stewardship; explaining quality and lineage issues to leaders; collaboration across product, AI, architecture, security, and risk; judgment on centralize vs. federate vs. reuse; problem-solving with incomplete or conflicting data; building reusable capabilities over one-off extracts.","description_format":"text","description_chars":4175,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Domain Registrars & Registries","Custody & Fund Administration","Brand Protection & Anti-Counterfeiting"],"lifecycle":[{"event":"open","at":"2026-09-28T14:20:17Z"},{"event":"close","at":"2026-10-01T12:09:52Z"}],"visa":[],"liveness":null,"pay":null,"html_url":"https://alion.io/job/csc-senior-data-engineer","json_url":"https://alion.io/job/csc-senior-data-engineer.json","meta":{"generated_at":"2026-10-04T09:37:30Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"search","counted_by":"address","units_charged":0,"used_today":0,"day_limit":null,"remaining_today":null,"minute_limit":null,"resets_at":"2026-10-05T00:00:00Z"}}}