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Snowflake-Lead Data Engineer

Snowflake-Lead Data Engineer

LumenDataBengaluru, Karnataka, India
12 days ago
Job description

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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