{"id":2920676,"url":"https://alion.io/job/auxoai-data-engineer-gcpdatabricks","title":"Data Engineer- GCP/Databricks","company":{"id":46892,"name":"AuxoAI","domain":"auxoai.com","url":"https://alion.io/company/auxoai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":{"grade":"A","score":89,"open_postings":8,"ghost_share":0,"stale_share":0.25,"repost_share":0,"time_to_fill_p50_days":76,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","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":22000,"max_usd":47000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Collibra","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Terraform","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-09-24T00:00:00Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-11-02T19:36:13Z","board_verified":true,"closed_at":null,"days_open":39,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":39},"description":"AuxoAI is seeking a Senior Data Engineer to lead the design, development, and optimisation of modern data pipelines and cloud-native platforms. This role is ideal for someone with deep experience building scalable batch and streaming data workflows across cloud and lakehouse environments, strong hands-on engineering skills, and a drive to mentor junior engineers.\nYou will work closely with AI engineers, solution architects, and cross-functional teams to build production-grade pipelines spanning ingestion, transformation, and curated data delivery - enabling high-quality data for AI and analytics use cases at scale.\nLocation: Bangalore / Mumbai / Hyderabad / Gurgaon (Hybrid - 3 days in office)\nResponsibilities\nDesign and build scalable batch and streaming data pipelines across bronze, silver, and gold medallion layers.\nBuild historical and incremental ingestion using Auto Loader/Spark Structured Streaming/Kafka feeds, with GCS/Azure/AWS storage and Databricks Jobs orchestration.\nDevelop and maintain Databricks-based pipelines using Spark and Delta Lake for lakehouse architecture, including migration of legacy or on-premises data sources.\nDesign and maintain analytical data layers in BigQuery or Databricks SQL, applying best practices in partitioning, clustering, and performance tuning.\nImplement SQL/PySpark transformations for wide and semi-structured data, including wide-to-long processing and typed or hybrid models suited to consumer requirements.\nCollaborate with AI engineers and data scientists to build pipelines that feed ML models, AI agents, and analytical systems.\nImplement data governance, quality controls, and security best practices including schema enforcement, lineage tracking, and access controls.\nDrive engineering best practices across CI/CD, testing, monitoring, and pipeline observability.\nPartner with solution architects to translate data requirements into technical designs.\nMentor junior data engineers and contribute to documentation, code reviews, and agile ceremonies.\nRequirements\n5+ years of hands-on experience in data engineering, building and operating production-grade pipelines.\nHands-on experience with Databricks on GCP, including BigQuery, GCS, Databricks, Spark, Delta Lake, and structured streaming.\nHands-on experience with Databricks and Apache Spark, including Delta Lake and end-to-end lakehouse implementations.\nStrong programming skills in Python and/or Scala, with solid SQL for modelling and transformation.\nExperience with data modelling, ETL/ELT, pipeline orchestration, and data warehousing concepts, including experience working with large, evolving JSON/map/array payloads, wide-to-long transformations, event-time context joins and schema-change handling.\nFamiliarity with Git, CI/CD pipelines, and data quality monitoring frameworks.\nSolid understanding of data architecture, schema design, and performance tuning.\nExperience with Unity Catalog, source reconciliation, schema evolution, correction handling and replay/recovery testing.\nStrong problem-solving and collaboration skills.\nBonus Skills\nGCP Professional Data Engineer certification.\nExperience with Vertex AI, Cloud Functions, Dataproc, or real-time streaming architectures.\nExperience with factory or industrial data sources - 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