{"id":1253126,"url":"https://alion.io/job/okda-solutions-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3800839,"name":"Okda Solutions","domain":"okdasolutions.com","url":"https://alion.io/company/okda-solutions","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":"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":{"min_usd":21000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":51},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"RAG","optional":false},{"name":"SharePoint","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true},{"name":"ETL/ELT","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-09-11T04:17:48Z","employer_posted_date":null,"last_verified_at":"2026-09-11T04:17:48Z","board_verified":false,"closed_at":null,"days_open":19,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":19},"description":"Job Summary :\n\nWe are looking for a Senior Data Engineer with 6+ years of experience in Databricks, real-time data processing, Lakehouse architecture, and AI-driven solutions. The role involves designing scalable batch and streaming data platforms and delivering high-quality, governed data and AI solutions.\n\nKey Responsibilities :\n\n- Design, develop, and maintain batch and streaming data pipelines using Databricks and PySpark.\n\n- Build, optimize, and manage Delta Lake tables within Unity Catalog.\n\n- Develop and support Lakeflow pipelines with incremental processing, CDC, and data quality validation.\n\n- Integrate SharePoint and other external enterprise data sources into the Databricks Lakehouse.\n\n- Ensure data quality, governance, security, reliability, and operational excellence.\n\n- Monitor, troubleshoot, and optimize data workflows for performance and reliability.\n\n- Collaborate with business and technical stakeholders to deliver scalable solutions.\n\n- Build AI-powered data solutions, copilots, and intelligent agents using LLMs, RAG, and vector search.\n\n- Implement CI/CD and automated deployment using Databricks Repos and Asset Bundles.\n\n- Drive deliverables independently and proactively resolve technical challenges.\n\nMandatory Skills :\n\n- 6+ years of Data Engineering experience.\n\n- Strong hands-on experience with Databricks and modern Lakehouse architecture.\n\n- Strong proficiency in PySpark, Spark Structured Streaming, and SQL.\n\n- Experience with Delta Lake, Unity Catalog, Databricks Workflows, and job orchestration.\n\n- Experience with Bronze, Silver, and Gold Lakehouse architecture.\n\n- Practical experience with Databricks Lakeflow, Declarative Pipelines, Lakeflow Connect, CDC, data quality, and incremental processing.\n\n- Experience integrating enterprise data platforms with AI-driven applications.\n\n- Experience with LLMs, RAG, vector search, and prompt engineering.\n\n- Strong understanding of automated deployment and release processes.\n\n- Experience with Git-based source control and CI/CD.\n\nData Governance & Security :\n\n- Unity Catalog governance and security.\n\n- Role-Based Access Control (RBAC).\n\n- Data masking and data protection policies.\n\n- Audit logging, data lineage, and compliance.\n\nDevOps & Deployment :\n\n- Git-based source control and CI/CD.\n\n- Databricks Repos.\n\n- Databricks Asset Bundles (DABs).\n\n- Automated deployment and release processes.\n\nPreferred Skills :\n\n- Experience with large-scale enterprise data platforms.\n\n- Strong understanding of Lakehouse and Data Mesh principles.\n\n- Exposure to Azure cloud services and enterprise integration patterns.\n\n- Experience with NoSQL databases.\n\n- Strong problem-solving, communication, and stakeholder management skills.\nSkills\nData Engineering, Databricks, Apache Spark, Python, SQL, ETL, DataLake, Data Governance, Data Quality, Data Validation, Azure Databricks","description_format":"text","description_chars":2867,"description_truncated":false,"requirements":{"experience_years_min":6,"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":[],"lifecycle":[{"event":"open","at":"2026-09-25T18:04:06Z"}],"liveness":{"score":45,"band":"ok","label":"Likely open","p_open":0.85,"p_active":0.702,"p_room":0.75,"age_days":19,"expected_fill_days":23,"reasons":["seen:19","velocity","win:late"],"computed_at":"2026-09-30T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/okda-solutions-senior-data-engineer","json_url":"https://alion.io/job/okda-solutions-senior-data-engineer.json","meta":{"generated_at":"2026-10-01T03:00:54Z","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":2451,"day_limit":5000,"remaining_today":2549,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}