Team Lead - Mumbai, India - SNV AVIATION PRIVATE LIMITED

    SNV AVIATION PRIVATE LIMITED
    SNV AVIATION PRIVATE LIMITED Mumbai, India

    2 weeks ago

    Default job background
    permanent Technology / Internet
    Description

    Job Position Summary :


    We are seeking an experienced and motivated Tech Lead for Data Engineering to oversee our data engineering team and drive the development of innovative data solutions.

    The Tech Lead will be responsible for leading the design, implementation, and optimization of data pipelines, architectures, and systems.

    The ideal candidate will have a strong background in data engineering, excellent leadership skills, and a passion for leveraging data to drive business outcomes.

    Key responsibilities :


    • Lead a team of data engineers in designing, building, and maintaining scalable and efficient data pipelines and systems.
    • Architect end-to-end data solutions, including data ingestion, processing, storage, and consumption, to meet business requirements and technical goals.
    • Collaborate with cross-functional teams, analysts, software engineers, and business stakeholders, to understand data needs and deliver high-impact solutions.
    • Define and enforce data engineering best practices, standards, and processes to ensure code quality, reliability, and scalability.
    • Mentor and coach team members, providing technical guidance, conducting code reviews, and fostering a culture of learning and innovation.
    • Stay current with emerging technologies and trends in data engineering, big data, and cloud computing, and evaluate their applicability to our data architecture.
    • Drive continuous improvement and optimization of data pipelines, systems, and processes to enhance performance, reliability, and efficiency.
    • Collaborate with DevOps and infrastructure teams to deploy and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud.
    • Lead the evaluation and adoption of new tools, frameworks, and technologies to enhance our data engineering capabilities and productivity.
    )