{"id":1265732,"url":"https://alion.io/job/raapid-inc-senior-data-engineer","title":"Senior Data Engineer","company":{"id":2987931,"name":"RAAPID INC","domain":"raapidinc.com","url":"https://alion.io/company/raapidinc","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"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":["Ahmedabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":27000,"max_usd":57000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":9},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Kubernetes","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-09T10:28:58Z","employer_posted_date":null,"last_verified_at":"2026-09-09T10:28:58Z","board_verified":false,"closed_at":null,"days_open":17,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":17},"description":"Role Summary :\n\nWe are hiring a Senior Data Engineer to drive the development of scalable, high-performance data pipelines for a migration project to a modern Azure Native architecture. This role will be instrumental in building an AI-ready data platform using Microsoft Fabric (Fabric IQ) and enabling seamless integration with AI/ML workflows (Foundry IQ).\n\nKey Responsibilities :\n\n- Design and build robust, scalable data pipelines (batch + near real-time) using Microsoft Fabric (Data Pipelines, Lakehouse).\n\n- Lead migration of existing pipelines (AKS/custom ETL) to Fabric-native architecture.\n\n- Implement Medallion Architecture (Bronze , Silver , Gold) for structured and unstructured healthcare data.\n\n- Develop and optimize data models and transformations for analytics and AI use cases.\n\n- Build ingestion frameworks for APIs (FHIR, EHR systems) and Files (JSON, HL7, CSV).\n\n- Ensure data quality, validation (FHIR/claims), and observability across pipelines.\n\n- Enable AI/ML workflows by preparing datasets for RAG pipelines and feature engineering.\n\n- Optimize pipeline performance, cost, and scalability.\n\n- Collaborate with Architects, AI/ML engineers, and Product teams to translate requirements into data solutions.\n\n- Mentor junior engineers and drive engineering best practices.\n\nTechnical Skills :\n\n- Languages : Python, PySpark, SQL (advanced).\n\n- Azure / Fabric : Microsoft Fabric (preferred) OR Azure Data Factory, Synapse, Data Lake.\n\n- Data Architecture : Lakehouse, Medallion Architecture, Batch + streaming data processing.\n\n- Data Handling : JSON, Parquet, CSV, API integrations.\n\n- Performance Optimization : Partitioning, indexing, query tuning.\n\nNice to Have :\n\n- Experience with healthcare data (FHIR, claims, EHR).\n\n- Exposure to RAG pipelines / vector databases / AI data prep.\n\n- Familiarity with event-driven architectures.\n\n- Understanding of data security & governance in regulated environments.\n\nWhat Were Looking For :\n\n- Strong hands-on engineer with ownership mindset.\n\n- Ability to operate in fast-paced, evolving architecture environment.\n\n- Problem-solver with focus on performance, scalability, and data quality.\n\n- Mentor and team player.\n\nSkills\nData Engineering, Data Pipeline, ETL, Medallion Architecture, Python, PySpark, Azure Data Factory, SQL, Azure","description_format":"text","description_chars":2303,"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":["Artificial Intelligence","Health Care","Care Coordination & Population Health"],"lifecycle":[{"event":"open","at":"2026-09-25T22:00:00Z"}],"liveness":{"score":60,"band":"ok","label":"Likely open","p_open":0.85,"p_active":0.783,"p_room":0.9,"age_days":16,"expected_fill_days":42,"reasons":["seen:16","win:mid"],"computed_at":"2026-09-26T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/raapid-inc-senior-data-engineer","json_url":"https://alion.io/job/raapid-inc-senior-data-engineer.json","meta":{"generated_at":"2026-09-27T03:19:01Z","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":3116,"day_limit":5000,"remaining_today":1884,"minute_limit":60,"resets_at":"2026-09-28T00:00:00Z"}}}