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    Job · 18305228

    Texplorers logo

    Lead Data Engineer

    Texplorers · Hyderabad · hybrid · Posted 33d ago

    Undisclosed8–13 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Job Title: Data Engineering Technical Lead
    Location: Hyderabad, Telangana
    Work Model: Hybrid

    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.

    Please note: This is a pure technical leadership role, focused on architecture and execution rather than project management or Scrum facilitation.

    The focus is on:
    • Technical direction
    • Engineering quality
    • Delivery execution
    • Removing technical blockers
    • Ensuring consistency and scalability across teams

    The Technical Lead will act as the bridge between architecture, engineering teams, and delivery, while remaining capable of hands-on contribution when needed.

    Key Responsibilities
    Technical Leadership & Coordination
    • Act as the technical reference point for data engineers during migration and transformation activities
    • Break down high-level migration objectives into clear technical tasks and implementation approaches
    • Ensure alignment to target architecture and standards (Databricks, cloud-native patterns)
    • Review designs, pipelines, and implementations to ensure quality and consistency
    • Actively remove technical blockers for the engineering teams

    Migration & Transformation Execution

    Lead the migration of data pipelines from:
    o   SQL Server / SSIS (on-prem)
    o   Azure Synapse
    o   Azure SQL / SQL Managed Instances into Databricks (Lakehouse architecture)

    Define and enforce best practices for:
    o   Data ingestion
    o   Transformation patterns
    o   Performance optimization
    o   Cost awareness
    Support coexistence scenarios during the transition phase

    Hands-on Engineering (as needed)
    Contribute directly to development when required:
    o Databricks notebooks (PySpark / SQL)
    o Ingestion pipelines
    o Refactoring legacy logic
    Build reference implementations and examples for the team
    Support troubleshooting and performance tuning

    Team Enablement
    • Mentor data engineers and help upskill them towards Databricks and modern data engineering practices
    • Facilitate technical discussions, refinement sessions, and solution reviews
    • Ensure development stays on track, even across multiple parallel workstreams

    What This Role Is NOT
    • Not a Project Manager
    • Not a Scrum Master
    • Not a pure Architect
    • Not 100% hands-on developer
    It is a delivery-focused technical leadership role.

    Required Technical Skills
    Core Platform Knowledge
    • Strong experience in Data Engineering
    • Proven experience leading engineers in complex data environments
    • Hands-on experience with:
    o Databricks (mandatory)
    o PySpark & Spark SQL
    o Lakehouse concepts (Bronze / Silver / Gold)
    Microsoft & Azure Background (must-have due to migration context)

    Solid experience with:
    o SQL Server
    o Azure SQL / SQL Managed Instances
    o Azure Synapse
    • Ability to translate legacy ETL logic into modern Spark-based pipelines

    Cloud & Engineering Practices
    • Experience with Azure cloud environments
    • Understanding of:
    • CI/CD for data pipelines
    • Git-based development
    • Infrastructure-as-code concepts (nice to have)
    • Strong SQL skills
    • Performance tuning and troubleshooting experience

    Qualifications
    Bachelors or Master’s degree in Computer Science, or a strictly related technical discipline.
    8-12 years of specialized experience in Data Engineering.
    Preferred background in the Retail sector, with an understanding of industry-specific data challenges.

    Technical Leadership
    Lead the DE Team/Owning the DE tasks (Design, build, maintain entire pipelines)
    Data quality/Integrity/availability across the system


    Sourced from naukri

    Skills

    Azure SynapsePysparkSQLData WarehousingAzure Data FactoryAzure DatabricksETL

    Lead Data Engineer · waiting for your command