{"id":4091271,"url":"https://alion.io/job/texplorers-data-engineering-technical-lead","title":"Data Engineering Technical Lead","company":{"id":3800746,"name":"Texplorers","domain":"texplorers.com","url":"https://alion.io/company/texplorers","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":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Scrum","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-11-11T17:19:35Z","employer_posted_date":null,"last_verified_at":"2026-11-11T17:19:35Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"The Technical Lead will drive the migration of our Microsoft-based data platforms (on-premise and Azure) to Databricks, providing hands-on mentorship and technical oversight for the data engineering team.\n\nPlease note: This is a pure technical leadership role, focused on architecture and execution rather than project management or Scrum facilitation.\n\nThe focus is on:\n\nTechnical direction\nEngineering quality\nDelivery execution\nRemoving technical blockers\nEnsuring consistency and scalability across teams\n\nThe Technical Lead will act as the bridge between architecture, engineering teams, and delivery, while remaining capable of hands-on contribution when needed.\n\nKey Responsibilities\n\nTechnical Leadership & Coordination\n\nAct as the technical reference point for data engineers during migration and transformation activities\nBreak down high-level migration objectives into clear technical tasks and implementation approaches\nEnsure alignment to target architecture and standards (Databricks, cloud-native patterns)\nReview designs, pipelines, and implementations to ensure quality and consistency\nActively remove technical blockers for the engineering teams\n\nMigration & Transformation Execution\n\nLead the migration of data pipelines from:\no SQL Server / SSIS (on-prem)\n\no Azure Synapse\n\no Azure SQL / SQL Managed Instances→ into Databricks (Lakehouse architecture)\n\nDefine and enforce best practices for:\no Data ingestion\n\no Transformation patterns\n\no Performance optimization\n\no Cost awareness\n\nSupport coexistence scenarios during the transition phase\n\nHands-on Engineering (as needed)\n\nContribute directly to development when required:\nDatabricks notebooks (PySpark / SQL)\nIngestion pipelines\nRefactoring legacy logic\nBuild reference implementations and examples for the team\nSupport troubleshooting and performance tuning\n\nTeam Enablement\n\nMentor data engineers and help upskill them towards Databricks and modern data engineering practices\nFacilitate technical discussions, refinement sessions, and solution reviews\nEnsure development stays on track, even across multiple parallel workstreams\nWhat This Role Is NOT\n\n Not a Project Manager\n Not a Scrum Master\n Not a pure Architect\n Not 100% hands-on developer\nIt is a delivery-focused technical leadership role.\n\nRequired Technical Skills\n\nCore Platform Knowledge\n\nStrong experience in Data Engineering\nProven experience leading engineers in complex data environments\nHands-on experience with:\nDatabricks (mandatory)\nPySpark & Spark SQL\nLakehouse concepts (Bronze / Silver / Gold)\nMicrosoft & Azure Background (must-have due to migration context)\n\nSolid experience with:\nSQL Server\nAzure SQL / SQL Managed Instances\nAzure Synapse\nAbility to translate legacy ETL logic into modern Spark-based pipelines\nCloud & Engineering Practices\n\nExperience with Azure cloud environments\nUnderstanding of:\nCI/CD for data pipelines\nGit-based development\nInfrastructure-as-code concepts (nice to have)\nStrong SQL skills\nPerformance tuning and troubleshooting experience\n\nQualifications\n\nBachelor's or Master's degree in Computer Science, or a strictly related technical discipline.\n\n7-10 years of specialized experience in Data Engineering.\n\nPreferred background in the Retail sector, with an understanding of industry-specific data challenges.\n\nTechnical Leadership\n\nLead the DE Team/Owning the DE tasks (Design, build, maintain entire pipelines)\n\nData quality/Integrity/availability across the system","description_format":"text","description_chars":3448,"description_truncated":false,"requirements":{"experience_years_min":7,"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":["Analytics & BI Consulting","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-11-11T20:09:00Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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