{"id":3316031,"url":"https://alion.io/job/lufthansa-technik-data-engineer-azure-databricks","title":"Data Engineer (Azure & Databricks)","company":{"id":1873628,"name":"Lufthansa Technik","domain":"lufthansa-technik.com","url":"https://alion.io/company/lufthansa-technik","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":null,"employment_type":"full_time","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":17500,"max_usd":48000,"period":"year","method":"role_country_seniority_unknown","sample_n":171},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"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":"Kubernetes","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-26T23:34:17Z","employer_posted_date":null,"last_verified_at":"2026-10-26T23:34:17Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Role Overview\n\nWe are seeking a highly skilled Data Engineer with strong experience in Azure and Databricks, who will play a critical role in designing, transforming, and operationalizing data pipelines within a modern Lakehouse architecture.\n\nThe role primarily focuses on transforming data from the Bronze layer into curated analytics-ready datasets, building automated CI/CD pipelines, and developing high-quality Python and PySpark-based data solutions. The engineer will also collaborate closely with Data Scientists and Software Engineers and should be open to contributing to data-driven UI/UX initiatives.\n\nData Engineering & Transformation\n\nDesign, develop, and maintain scalable data transformation pipelines using Python (with tools like PySpark, ADF) and SQL in Azure Databricks\nImplement transformation logic to move data from Bronze to Silver/Gold layers following data engineering best practices\nApply strong data engineering principles to ensure data reliability, quality, performance, and reusability\nWork with structured and semi-structured data at scale\n\nDatabricks, Azure & Cloud ETL\n\nBuild and manage Databricks notebooks, jobs, Delta Lake tables, and orchestrated workflows\nHands-on experience with Cloud-based ETL platforms\n\n(Preferred: Microsoft Azure Databricks, Synapse, Azure Functions; otherwise AWS or Google Cloud)\n\nOptimize data pipelines for performance, scalability, and cost efficiency\n\nPython Applications, APIs & Automation\n\nDesign, develop, and maintain Python applications, scripts, and APIs for data processing and automation\nWrite production-grade Python code with strong focus on readability, maintainability, and testing\nLeverage Python for orchestration, validation, and integration with downstream systems\n\nCollaboration with Data Science & Engineering Teams\n\nCollaborate closely with Data Scientists and Data Analysts to understand data, analytical models, and consumption requirements\nEnable and support advanced analytics and data science workflows by preparing high-quality feature datasets\nTranslate analytical needs into scalable data engineering solutions\n\nCI/CD, DevOps & Platform Engineering\n\nBuild and maintain automated CI/CD pipelines for data and Databricks workloads\nHands-on experience with DevOps tools and practices, including Git-based version control\nExposure to containerization and orchestration platforms such as Kubernetes / OpenShift\nEnsure smooth promotion of code and pipelines across environments (Dev/Test/Prod)\n\nData Modeling & Querying\n\nDesign and implement robust data models optimized for analytics and reporting\nStrong hands-on knowledge of SQL and exposure to KQL or other query languages\nApply best practices in data structures, indexing, and performance tuning UI / UX & Data Applications (Additional Advantage)\nOpen to contributing to data-driven UI/UX components, dashboards, or lightweight data applications\nWork with analytics and business teams to improve data usability and customer experience\n\nRequired Skills & Qualifications\n\nMust-Have\n\nStrong hands-on expertise in Python (with frameworks like PySpark)\nSolid foundation in Data Engineering principles and large-scale data processing\nExperience with Azure Databricks and cloud-based ETL platforms\nStrong knowledge of SQL and data querying techniques\nExperience with CI/CD pipelines and DevOps practices\nExperience in pipeline monitoring and alerting\nAbility to design efficient, scalable solutions to complex data problems\n\nGood-to-Have\n\nExperience with Azure Synapse, Azure Functions\nExposure to AWS or Google Cloud data platforms\nHands-on experience with OpenShift\nKnowledge of data science concepts and workflows\nFamiliarity with analytics platforms, dashboards, and UI/UX considerations","description_format":"text","description_chars":3729,"description_truncated":false,"requirements":{"experience_years_min":null,"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":["Commercial Aviation","Engineering Services"],"lifecycle":[{"event":"open","at":"2026-10-27T05:09:15Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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