Job Title: Data Engineer - Snowflake
Experience: 12–14 Years
Job Type: Contract
Location: [Remote / Hybrid / Onsite – TBD]
Job Summary:
We are looking for an experienced Senior Data Engineer with strong hands-on expertise in Snowflake to design, develop, and maintain scalable data engineering and cloud data warehouse solutions.
The ideal candidate will have 12–14 years of overall IT experience with strong experience in data engineering, data warehousing, ETL/ELT, SQL, and Snowflake. The candidate should be capable of working with large datasets, developing complex data pipelines, optimizing Snowflake environments, and collaborating with technical and business stakeholders.
Mandatory Skills:
Snowflake – Strong / Mandatory
· Strong hands-on experience with Snowflake Data Cloud.
· Strong experience with Snowflake architecture and data warehouse concepts.
· Advanced SQL skills.
· Experience with Snowflake Streams, Tasks, Snowpipe, Time Travel, and Zero-Copy Cloning.
· Experience with Snowflake performance tuning and query optimization.
· Experience with Snowflake security, roles, access control, and resource management.
· Experience designing and implementing Snowflake data models.
Key Responsibilities:
· Design, develop, and maintain scalable data pipelines and data warehouse solutions using Snowflake.
· Develop complex ETL/ELT pipelines for ingesting and transforming data from multiple sources.
· Design and implement data models for analytical and reporting requirements.
· Develop complex SQL queries, stored procedures, views, and data transformation logic.
· Perform data ingestion into Snowflake from various structured and unstructured data sources.
· Optimize Snowflake queries, warehouses, tables, and data pipelines for performance and cost efficiency.
· Implement Snowflake features such as Streams, Tasks, Snowpipe, Time Travel, and Zero-Copy Cloning.
· Develop and maintain automated data loading and transformation workflows.
· Work with cloud storage and cloud-based data platforms for data integration.
· Implement data quality, validation, reconciliation, and error-handling processes.
· Troubleshoot data pipeline and production issues.
· Collaborate with Data Architects, Data Scientists, Analysts, Developers, and business stakeholders.
· Participate in technical design, code reviews, testing, deployment, and production support.
· Follow best practices for data security, governance, scalability, and performance.
· Mentor junior and mid-level data engineers and provide technical guidance.
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