{"id":1252232,"url":"https://alion.io/job/lufthansa-technik-services-india-data-engineer","title":"Data Engineer","company":{"id":3800300,"name":"Lufthansa Technik Services India","domain":"lht-services-india.com","url":"https://alion.io/company/lufthansa-technik-services-india","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":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, 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Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-15T10:43:03Z","employer_posted_date":null,"last_verified_at":"2026-09-15T10:43:03Z","board_verified":false,"closed_at":null,"days_open":28,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":28},"description":"Role & Responsibilities:\n\nData Engineering & Transformation:\n\n- Design, develop, and maintain scalable data transformation pipelines using Python (with tools like PySpark, ADF) and SQL in Azure Databricks.\n\n- Implement transformation logic to move data from Bronze to Silver/Gold layers following data engineering best practices.\n\n- Apply strong data engineering principles to ensure data reliability, quality, performance, and reusability.\n\n- Work with structured and semi-structured data at scale.\n\nDatabricks, Azure & Cloud ETL:\n\n- Build and manage Databricks notebooks, jobs, Delta Lake tables, and orchestrated workflows.\n\n- Hands-on experience with Cloud-based ETL platforms (Preferred: Microsoft Azure Databricks, Synapse, Azure Functions; otherwise AWS or Google Cloud).\n\n- Optimize data pipelines for performance, scalability, and cost efficiency.\n\nPython Applications, APIs & Automation:\n\n- Design, develop, and maintain Python applications, scripts, and APIs for data processing and automation.\n\n- Write production-grade Python code with strong focus on readability, maintainability, and testing.\n\n- Leverage Python for orchestration, validation, and integration with downstream systems.\n\nCollaboration With Data Science & Engineering Teams:\n\n- Collaborate closely with Data Scientists and Data Analysts to understand data, analytical models, and consumption requirements.\n\n- Enable and support advanced analytics and data science workflows by preparing high-quality feature datasets.\n\n- Translate analytical needs into scalable data engineering solutions.\n\nCI/CD, DevOps & Platform Engineering:\n\n- Build and maintain automated CI/CD pipelines for data and Databricks workloads.\n\n- Hands-on experience with DevOps tools and practices, including Git-based version control.\n\n- Exposure to containerization and orchestration platforms such as Kubernetes / OpenShift.\n\n- Ensure smooth promotion of code and pipelines across environments (Dev/Test/Prod).\n\nData Modeling & Querying:\n\n- Design and implement robust data models optimized for analytics and reporting.\n\n- Strong hands-on knowledge of SQL and exposure to KQL or other query languages.\n\n- Apply best practices in data structures, indexing, and performance tuning.\n\nUI / UX & Data Applications (Additional Advantage):\n\n- Open to contributing to data-driven UI/UX components, dashboards, or lightweight data applications.\n\n- Work with analytics and business teams to improve data usability and customer experience.\n\nPreferred Candidate Profile:\n\nMust-Have:\n\n- Strong hands-on expertise in Python (with frameworks like PySpark).\n\n- Solid foundation in Data Engineering principles and large-scale data processing.\n\n- Experience with Azure Databricks and cloud-based ETL platforms.\n\n- Strong knowledge of SQL and data querying techniques.\n\n- Experience with CI/CD pipelines and DevOps practices.\n\n- Experience in pipeline monitoring and alerting.\n\n- Ability to design efficient, scalable solutions to complex data problems.\n\nGood-to-Have:\n\n- Experience with Azure Synapse, Azure Functions.\n\n- Exposure to AWS or Google Cloud data platforms.\n\n- Hands-on experience with OpenShift.\n\n- Knowledge of data science concepts and workflows.\n\n- Familiarity with analytics platforms, dashboards, and UI/UX considerations.\nSkills\nPython, Azure Databricks, PySpark, Delta Lake, Data Engineering, KQL, Synapse 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