{"id":3388061,"url":"https://alion.io/job/weekday-senior-data-engineer-4","title":"Senior Data Engineer","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":92,"ghost_share":0,"stale_share":0.978,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Pune, 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":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false}],"status":"closed","first_seen_at":"2026-10-28T08:40:56Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-02T20:44:05Z","board_verified":false,"closed_at":"2026-11-02T20:44:05Z","days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"This role is for one of Weekday’s clients\nMin Experience: 3.5+ years\nLocation: India, Pune\nJobType: full-time\nWe are looking for an experienced Senior Data Engineer with 3.5+ years of experience in designing, developing, and maintaining scalable data pipelines and robust data engineering solutions. The ideal candidate will have strong expertise in Databricks, Azure Data Services, and programming languages such as Python and Scala. You will be responsible for building efficient data processing workflows, optimizing data performance, and ensuring data quality, security, and reliability across the data platform.\nThe role requires hands-on experience with Lakehouse architecture, Delta Lake, Unity Catalog, and ETL/ELT processes. You should be comfortable working with large datasets, troubleshooting production issues, and implementing best practices for data governance, automation, and performance optimization.\nRequirements\nKey Responsibilities\nDesign, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and/or Scala.\nBuild and optimize data ingestion, transformation, and processing workflows using ETL/ELT methodologies.\nImplement and maintain Lakehouse architecture and Delta Lake solutions to support reliable and efficient data storage and processing.\nWork with Azure cloud services, particularly Azure Data Lake Storage Gen2 (ADLS Gen2), to manage and process large volumes of data.\nOptimize Spark jobs and data pipelines for performance, scalability, and cost efficiency.\nImplement data modeling practices to support analytical workloads, reporting, and downstream data consumption.\nUse Unity Catalog and related governance capabilities to manage data access, security, permissions, and compliance.\nDevelop and maintain CI/CD pipelines to automate deployment, testing, and release processes for data engineering solutions.\nMonitor production data pipelines, troubleshoot failures, and resolve performance and data quality issues.\nCollaborate with data scientists, analysts, architects, and other engineering teams to deliver dependable data solutions.\nFollow best practices for data quality, documentation, version control, security, and production support.\nMust-Have Skills\nStrong hands-on experience with Databricks and Azure data engineering services.\nExperience working with Azure Data Lake Storage Gen2 (ADLS Gen2).\nProficiency in Python and/or Scala for data processing and pipeline development.\nMinimum 3.5 years of relevant experience in data engineering.\nStrong understanding of data pipeline development, data integration, and cloud-based data platforms.\nExperience with CI/CD workflows, data modeling, governance, and production support.\nGood-to-Have Skills\nHands-on experience with Apache Spark and distributed data processing.\nKnowledge of Delta Lake, Unity Catalog, and Lakehouse architecture.\nExperience with ETL/ELT development and data transformation frameworks.\nExpertise in Spark performance tuning, query optimization, and efficient resource utilization.\nFamiliarity with data quality monitoring, pipeline orchestration, and automated testing.\nExperience and Qualifications\n Experience: 3.5+ years in data engineering or a related field.\nStrong analytical and problem-solving skills, with the ability to troubleshoot complex data issues.\nAbility to work collaboratively in a fast-paced environment and take ownership of data engineering deliverables.\nA focus on building scalable, secure, maintainable, and production-ready data 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