Sr.Data Engineer/ Architect

Job Title: Sr.Data Engineer/ Architect Location: Onsite - Las Vegas Job Type: Contract Job Description: Expereince Range : 10+ Years Must Required Skils: Skills - Strong in Python ; Snowflake ; SQL Primary Responsibilities: • Data Architecture & Design: Define and implement enterprise-scale data architecture blueprints within the Snowflake ecosystem, ensuring alignment with financial services security and performance standards. • Pipeline Engineering: Design, build, and maintain end-to-end ELT/ETL pipelines using Python (and PySpark) to automate the ingestion and transformation of large, complex financial datasets. • Warehouse Optimization: Lead performance tuning efforts by leveraging Snowflake-specific features such as clustering keys, micro-partitioning, and query profile analysis to handle high-concurrency transaction volumes. • Data Modernization: Partner with Risk Technology and other internal stakeholders to migrate legacy data process flows into modern, scalable cloud-native solutions. • Security & Governance: Implement robust data security measures, including Role-Based Access Control (RBAC), dynamic data masking, and row-access policies to protect sensitive cardholder information. • Workflow Automation: Orchestrate complex data flows using tools like Snowpipe, Streams, and Tasks to ensure real-time or micro-batch data availability. Required Skills: • Snowflake Mastery: Deep expertise in Snowflake’s three-layer architecture (Storage, Compute, Services), Snowpark, Zero-Copy Cloning, and Time Travel. • Expert Python: Advanced proficiency in Python for data processing, automation, and script development, with a strong grasp of data-centric libraries. • Advanced SQL: Expert-level SQL skills for complex data manipulation, window functions, and advanced performance optimization. • Data Modeling: Strong experience in Dimensional Modeling (Star and Snowflake schemas) specifically for large-scale enterprise environments. • Cloud Infrastructure: Familiarity with AWS services (e.g., S3, Glue, EMR) as they integrate with the Snowflake data lake. • Analytical Problem Solving: Ability to perform root cause analysis on data bottlenecks and translate business requirements into technical specs.