{"id":1428165,"url":"https://alion.io/job/accuris-data-engineer","title":"Data Engineer","company":{"id":11708,"name":"Accuris","domain":"accuristech.com","url":"https://alion.io/company/accuris","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","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":16000,"max_usd":38000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Angular","optional":true},{"name":"CI/CD","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"Git","optional":true},{"name":"JavaScript","optional":true},{"name":"LLM","optional":true},{"name":"pySpark","optional":true},{"name":"React.js","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-09-28T23:36:48Z","employer_posted_date":null,"last_verified_at":"2026-09-28T23:36:48Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Senior Associate 2 – Data Engineer | Location: Bangalore, IN\n\nExperience: 4–6 years relevant industry experience\n\nWhy Work for Accuris \n\nAccuris works on high-value, real-world data problems where reliability and correctness matter. You'll build production-grade data and GenAI systems that power decision-support products used by global customers. This is not experimental AI — this is measurable, grounded, and scalable AI backed by robust data engineering.\n\nRole Summary\n\nYou will design and own data pipelines and GenAI-driven services that transform messy enterprise data into high-quality datasets and production-ready product capabilities. This role requires strong data engineering depth, with the ability to build and integrate backend APIs and contribute to frontend integrations when needed. You will work across data, applications, and AI layers to ship scalable systems end-to-end.\n\nWhat You'll Do\n\nDesign and own ETL/ELT pipelines (batch and streaming where required).\nDrive Medallion architecture design (Bronze, Silver, Gold) with clear data contracts and quality checks.\nBuild scalable transformations using Spark/Databricks with performance tuning.\nImplement data validation frameworks, monitoring, lineage, and observability.\nHandle schema evolution, incremental loads, idempotency, and orchestration patterns.\nCollaborate with content and application teams to define reliable data models.\n\nMust Have\n\n4–6 years experience in Data Engineering / Backend Engineering.\nStrong Python and advanced SQL skills.\nHands-on Spark/Databricks experience with performance optimization.\nDeep understanding of Medallion architecture and production data systems.\nExperience building reliable data pipelines with testing and monitoring. Practical understanding of LLMs, RAG systems, embeddings, vector search. Experience building and deploying REST APIs. Understanding of system design basics (scalability, reliability, trade-offs).\n\nNice to Have\n\nFrontend exposure (React/Angular or similar).\nExperience with API gateways and microservices architecture.\nExperience with CI/CD pipelines and containerization (Docker).\nExperience with evaluation frameworks for GenAI systems. Knowledge of cost optimization in cloud-based data platforms.\nExperience with RAG systems\nContribute to architecture decisions around AI services and integration patterns.\n\nTech Stack \n\nPython, SQL, PySpark, Databricks, Delta Lake, orchestration tools, REST APIs (FastAPI), vector search systems, LLM APIs, Git, CI/CD, monitoring/logging, basic frontend frameworks.\n\nSuccess Looks Like \n\nYou independently design and ship production-grade pipelines.\nYou improve RAG quality through measurable retrieval and prompt improvements.\nYou build backend services that are scalable, observable, and secure.\nYou reduce data defects through better modeling and validation practices.\nYou proactively identify foundational gaps and address them before feature work scales.\n\nExperience That Stands Out\n\nBuilt and maintained a multi-layer medallion architecture at scale.\nDesigned and deployed a production RAG system with measurable evaluation.\nBuilt backend APIs serving AI/data features consumed by frontend apps.\nImproved system performance through Spark optimization or query tuning.\nContributed to cross-team architectural improvements.","description_format":"text","description_chars":3304,"description_truncated":false,"requirements":{"experience_years_min":4,"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":["Energy & Utilities","Manufacturing","Supply Chain"],"lifecycle":[{"event":"open","at":"2026-09-29T00:08:44Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":2,"expected_fill_days":18,"reasons":["seen:2","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/accuris-data-engineer","json_url":"https://alion.io/job/accuris-data-engineer.json","meta":{"generated_at":"2026-10-01T09:30:55Z","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":"crawler","counted_by":"address","units_charged":1,"used_today":131,"day_limit":5000,"remaining_today":4869,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}