{"id":2788232,"url":"https://alion.io/job/mercedes-benz-azure-databricks-platform-engineer","title":"Azure Databricks Platform Engineer","company":{"id":136,"name":"Mercedes-Benz","domain":"mercedes-benz.com","url":"https://alion.io/company/mercedes-benz","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career sitemap","truth_index":{"grade":"A","score":96,"open_postings":27,"ghost_share":0,"stale_share":0.111,"repost_share":0.074,"time_to_fill_p50_days":29,"computed_at":"2026-10-22T06:10:10Z"}},"role":"DevOps","role_family":"DevOps","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":["Bengaluru, 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":49},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"IAM","optional":false},{"name":"Platform Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Power BI","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-16T00:00:00Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-22T14:18:59Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Aufgaben\n Role: Azure Databricks Platform Engineer\nRole Description\nSupport the Platform Team in designing, implementing, and scaling Azure and Databricks-based data and platform solutions. The role combines hands-on engineering with platform ownership, automation, team collaboration, and continuous improvement.\nKey Responsibilities\nDesign, build, and maintain scalable Azure services and Azure Databricks solutions.\nDevelop and optimize ETL/ELT pipelines using Python, PySpark, and SQL.\nSupport GitHub, CI/CD, IAM, security, monitoring, and platform configurations.\nDrive platform automation, standardization, reusability, and optimization.\nExplore AI, LLMs, and emerging technologies to build and scale solutions and present relevant ideas to the team.\nCollaborate with cross-functional teams and guide team members on technical topics.\nQualifikationen\n Required Skills\n5+ years of experience in Data Engineering, Platform Engineering, or a similar role.\nStrong hands-on experience with Azure Services and Azure Databricks.\nExperience in solution/component design and development, including participation in or leading technical design reviews.\nStrong proficiency in Python, PySpark, and SQL.\nStrong understanding of ETL/ELT, data pipelines, data modeling, and data architecture.\nGood knowledge of Git, GitHub, CI/CD, and automated deployment practices.\nExperience with Python package management and release processes, including building and deploying Wheel packages.\nHands-on experience with Pytest and automated unit, integration, and regression testing.\nExperience with IAM, cloud security, Key Vault, Storage, and monitoring.\nUnderstanding of Data Governance, Data Quality, and Databricks Unity Catalog.\nKnowledge of AI and LLMs and their application in building and scaling solutions.\nStrong problem-solving, communication, collaboration, stakeholder management, and team coordination skills.\nGood to Have\nExperience with Azure Web Apps / App Services.\nKnowledge of Infrastructure as Code (IaC) and Declarative Asset Bundles.\nExposure to streaming technologies, MLOps, and Power 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