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Description
We are seeking a Lead Data Engineer - Snowflake with strong hands-on expertise in building and scaling modern data platforms. The ideal candidate will have deep experience working with Snowflake, strong data engineering fundamentals, and the ability to translate business requirements into scalable data solutions.
In this role, you will lead the design and implementation of Snowflake-based data platforms, develop robust data pipelines, and provide technical guidance to engineering teams while ensuring high performance, scalability, and reliability of data systems.
Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in :
- Lead the design, development, and optimization of data solutions built on the Snowflake data platform.
- Design and implement scalable data pipelines to ingest and process structured, semi-structured, and unstructured data from multiple sources.
- Work closely with stakeholders to understand business requirements and translate them into efficient data architectures and engineering solutions.
- Develop and optimize Snowflake data models, storage structures, and query performance using best practices such as clustering, partitioning, and warehouse scaling.
- Implement automated ingestion pipelines using Snowpipe and other orchestration mechanisms.
- Develop robust ETL/ELT processes and ensure efficient data transformation workflows.
- Implement governance, access control, and monitoring mechanisms including RBAC, resource monitors, and workload management.
- Optimize performance through query tuning, warehouse sizing, and micro-partition management.
- Collaborate with cross-functional teams including data scientists, analysts, product managers, and application developers to enable data-driven initiatives.
- Build monitoring and automation frameworks for Snowflake environments using tools such as Python, PySpark, Bash, and SnowSQL.
- Participate in migration initiatives from legacy or on-premise data platforms to Snowflake-based cloud architectures.
- Continuously improve data engineering standards, modeling principles, and platform best practices.
Requirements
- 5-10 years of experience in data engineering or data platform development.
- Strong hands-on experience with the Snowflake data platform, including warehouse configuration, RBAC, query optimization, time travel, zero-copy cloning, and resource monitoring.
- Experience designing and implementing data pipelines and ETL/ELT workflows for enterprise-scale data platforms.
- Strong experience handling semi-structured data formats such as JSON, XML, and Parquet using Snowflake VARIANT data types.
- Understanding of Snowflake micro-partitioning, clustering, and performance optimization techniques.
- Experience building ingestion pipelines using Snowpipe or similar mechanisms.
- Hands-on experience with cloud platforms such as AWS including services like S3, SQS, EC2, Lambda, Redshift, or RDS.
- Strong programming skills in SQL and Python; familiarity with PySpark or Bash scripting is a plus.
- Experience developing automation, monitoring, and operational processes for Snowflake environments.
- Experience working on data platform migrations from on-premise systems to Snowflake.
- Strong problem-solving skills and the ability to collaborate effectively with technical and business stakeholders.
Nice To Have
- Snowflake certification (SnowPro Core).
- Experience working with modern data stack tools such as dbt, Airflow, or similar orchestration frameworks.
- Experience in consulting or client-facing delivery environments.
(ref:hirist.tech)
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