Data Engineer, Analytics

Snowflake SQL Data Modeling Snowflake Data Engineer Snowflake InvestmentData Platform Implementation Role Purpose The SnowflakeData Engineer will design, build, test, and optimize data pipelines, datamodels, and transformation logic within Snowflake to support investment dataconsolidation, reporting, analytics, governance, and historical databackfill. Domain Focus Investment data,public/private assets, historical backfill, portfolio reporting, dataquality, and controlled delivery. Snowflake, clouddata platform, ETL/ELT, data integration, governance, reconciliation, andBI/reporting consumption. Delivery Context Sensitivefinancial data environment; structured phased delivery with formalgovernance, sign-offs, and transition to support. Key Responsibilities Build Snowflake data pipelines,tables, views, procedures, tasks, streams, and transformation logic. Implement ingestion, staging,cleansing, transformation, enrichment, and consumption layers. Develop source-to-targetmappings for investment, portfolio, accounting, market data, reference data,and operational data sources. Build reusable data models forportfolios, holdings, transactions, instruments, valuations, cash, entities,performance, and historical records. Support public and privateinvestment data structures, including historical backfill and reconciliationrequirements. Implement data-quality checks,exception handling, audit fields, reconciliation logic, and validation rules. Optimize Snowflake performance,including warehouse usage, clustering, query design, data loading, andcost-aware engineering. Support data securityrequirements, including role-based access, masking, secure views, and datasegregation. Work closely with BusinessAnalysts, Solution Architect, Integration Engineer, Data Governance Lead, andTest Lead. Prepare technicaldocumentation, deployment scripts, data dictionaries, and handover materials. Required Experience 4+ years of data engineeringexperience, with strong hands-on experience in Snowflake. Experience building datapipelines, ELT processes, data models, and analytical data layers. Strong SQL skills andexperience with complex transformations. Experience working withinvestment, financial-services, accounting, portfolio, or market data ispreferred. Experience with historical datamigration, backfill, reconciliation, and data-quality validation. Experience with ETL/ELT tools,orchestration, cloud storage, APIs, and BI/reporting consumption layers. Familiarity with datagovernance, lineage, access control, and sensitive financial data.#J-18808-Ljbffr