Snowflake-Lead Data Engineer

3 hours ago

Bengaluru, Karnataka, India LumenData Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Key Responsibilities

  • Lead the design, development, and optimization of data pipelines and data warehouse solutions on
    Snowflake
    .
  • Snowflake -
    Types of Tables, Storage Integration, Internal & External Stages, Streams, Tasks, Views, Materialized Views, Time Travel, Fail Safe, Micro partitions, Warehouses, RBAC, COPY Command, File Formats (CSV, JSON and XML), snowpipe
    ,
    Stored Procedures (SQL or JavaScript, Python).
  • Develop and maintain
    dbt models
    for data transformation, testing, and documentation.
  • dbt –
    create, run and build a model, Scheduling, Running dependency Models, Macros,
    Jinga Template (Optional)
  • Collaborate with cross-functional teams including data architects, analysts, and business stakeholders to deliver robust data solutions.
  • Ensure high standards of data quality, governance, and security across pipelines and platforms.
  • Leverage
    Airflow
    (or other orchestration tools) to schedule and monitor workflows.
  • Integrate data from multiple sources using tools like
    Fivetran, Qlik Replicate, IDMC (At least one).
  • Provide technical leadership, mentoring, and guidance to junior engineers in the team.
  • Optimize costs, performance, and scalability of cloud-based data environments.
  • Contribute to architectural decisions, code reviews, and best practices.
  • CI/CD –
    BitBucket, GitHub (At least one).
  • Data Model –
    ENTITY (SUB DIM, DIM, FACTS), Data Vault (HUB, LINK, SAT).

Required Skills & Experience

  • 8–12 years of overall experience in Data Engineering, with at least 3–4 years in a
    lead role
    .
  • Strong hands-on expertise in
    Snowflake
    (data modeling, performance tuning, query optimization, security, and cost management).
  • Proficiency in
    dbt
    (core concepts, macros, testing, documentation, and deployment).
  • Solid programming skills in
    Python
    (for data processing, automation, and integrations).
  • Experience with workflow orchestration tools such as
    Apache Airflow
    .
  • Exposure to ELT/ETL tools.
  • Strong understanding of modern data warehouse architectures, data governance, and cloud-native environments.
  • Excellent problem-solving, communication, and leadership skills.

Good to Have

  • Hands-on experience with
    Databricks
    (PySpark, Delta Lake, MLflow).
  • Exposure to other cloud platforms (AWS, Azure, or GCP).
  • Experience in building CI/CD pipelines for data workflows.

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