Sr.Data Engineer/ Architect
Occupations:
Data Warehousing SpecialistsDatabase ArchitectsComputer Systems Engineers/ArchitectsSoftware DevelopersData ScientistsIndustries:
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related ServicesWeb Search Portals, Libraries, Archives, and Other Information ServicesManagement, Scientific, and Technical Consulting ServicesDrugs and Druggists' Sundries Merchant WholesalersTravel Arrangement and Reservation ServicesJob Title: Sr.Data Engineer/ Architect Location: Onsite - Las VegasJob Type: ContractJob Description:Expereince Range : 10+ YearsMust Required Skils: Skills - Strong in Python ; Snowflake ; SQLPrimary 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.