Senior Data Engineer
2 weeks ago
Required Work Experience - 7 - 12 Years - Total: 6+ years in Data Engineering, Data Warehousing, and SQL - Snowflake: 3+ years hands-on experience Primary Responsibilities: - Design and implement scalable Data Warehouse solutions using Snowflake as the core platform. - Understand the difference between Snowflake and traditional data warehouse system - Develop and optimize complex SQL queries for analytical workloads, reporting, and data transformation. - Build and maintain ELT/ETL pipelines using Snowflake-native features and external orchestration tools. - Apply dimensional modeling techniques (Star/Snowflake schemas) to support BI and analytics use cases. - Perform query profiling, performance tuning, and cost optimization in Snowflake. - Implement and manage Snowflake objects including tables, views, materialized views, streams, tasks, UDFs and Stored procedures. - Ensure data quality, lineage, and governance across the data lifecycle. - Collaborate with cross-functional teams to understand data requirements and translate them into efficient data models and pipelines. - Troubleshoot and resolve issues related to data ingestion, transformation, and query performance. - Stay current with Snowflake features such as Time Travel, Zero Copy Cloning, Search Optimization, and Streams/Tasks. Primary Technical Skills (Must-Have): - Advanced SQL – joins, window functions, CTEs, recursive queries, analytical functions - Snowflake SQL & Architecture – virtual warehouses, micro-partitions, clustering, caching, caling, max concurrency - Data Modeling – Star/Snowflake schemas, normalization/denormalization strategies - Performance Tuning – query optimization, warehouse sizing, result caching - ETL/ELT Development – using Snowflake-native features using stages and orchestration tools (ADF, Airflow, etc.) - Stored Procedures & Functions – SQL and JavaScript-based scripting in Snowflake and exception handling Secondary Technical Skills (Good or Nice to Have): - Azure Data Factory (ADF) – pipelines, triggers, ADLS Gen2, IR, Linked Services - Python or PySpark – for data transformation and automation - Snowpipe & Streams/Tasks – for real-time and CDC-based ingestion - Data Security – row-level security, masking policies, encryption hierarchy - DevOps Tools – Git, CI/CD, Terraform (basic understanding) Soft Skills & Methodologies: - Strong analytical and problem-solving skills - Excellent communication and documentation abilities - Experience working in Agile/Scrum environments - Ability to lead and mentor junior team members - Comfortable working in fast-paced, multi-project environments Education & Certifications: - Bachelor’s or Master’s in Computer Science, Engineering, or related field - SnowPro Core Certification is a plus
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