{"id":2263217,"url":"https://alion.io/job/adesso-databricks-data-engineer","title":"Databricks Data Engineer","company":{"id":51690,"name":"Adesso","domain":"adesso.de","url":"https://alion.io/company/adesso","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"B","score":80,"open_postings":23,"ghost_share":0,"stale_share":0.783,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-10T05:45:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, 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Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-11T22:33:52Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"YOUR ROLE\nDesign, develop, and maintain scalable batch and real-time data pipelines using Databricks, PySpark, and Spark SQL.\nBuild and implement Delta Lake-based solutions, including data ingestion, transformation, and Medallion Architecture (Bronze, Silver, Gold) layers.\nDevelop and orchestrate end-to-end data workflows using Databricks Workflows and other scheduling tools.\nOptimize Spark workloads for performance, scalability, and cost efficiency through effective cluster management and tuning practices.\nEnsure data quality, reliability, and governance through validation, monitoring, and testing frameworks.Integrate and process data from multiple enterprise sources, including databases, APIs, files, and streaming platforms.\nCollaborate with cross-functional teams, including data scientists, analysts, architects, and business stakeholders, to deliver data-driven solutions.\nContribute to code management, CI/CD implementation, documentation, and continuous improvement initiatives.\n YOUR PROFILE\n4-6 years of experience in Data Engineering, with strong hands-on expertise in Databricks.\nProficiency in Python, PySpark, and SQL for building scalable data processing solutions.\nStrong understanding of Apache Spark architecture, Delta Lake, and modern data engineering practices.\nExperience working with cloud platforms such as Azure, AWS, or GCP.Solid knowledge of ETL/ELT processes, data modeling, and data warehousing concepts.\nExperience with version control systems such as Git and CI/CD processes.\nFamiliarity with technologies such as Unity Catalog, Azure Data Factory, ADLS Gen2, Kafka, Event Hubs, Structured Streaming, or Snowflake is an advantage.\nExposure to Infrastructure-as-Code tools such as Terraform is a plus.Databricks certifications will be considered an added advantage.\nBachelor's degree in Computer Science, Information Technology, or a related field.","description_format":"text","description_chars":1887,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Custom Software 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