Senior data engineer
4 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 Java Script-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 Py Spark – for data transformation and automation Snowpipe & Streams/Tasks – for real-time and CDC-based ingestion Data Security – row-level security, masking policies, encryption hierarchy Dev Ops 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 Snow Pro Core Certification is a plus
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