Snowflake Data Engineer
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Key skills for this role
About the Role
Capgemini seeks a Snowflake Data Engineer to build data pipelines, tables, views, and transformation logic on Snowflake. Requires 4+ years of data engineering experience with strong Snowflake and SQL skills, preferably in financial services.
Key Skills for This Role
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 target mappings for investment, portfolio, accounting, market data, reference data, and operational data sources
- Build reusable data models for portfolios, holdings, transactions, instruments, valuations, cash, entities, performance, and historical records
- Support public and private investment data structures, including historical backfill and reconciliation requirements
- Implement data quality checks, exception handling, audit fields, reconciliation logic, and validation rules
- Optimize Snowflake performance, including warehouse usage, clustering, query design, data loading, and cost aware engineering
- Support data security requirements, including role based access, masking, secure views, and data segregation
- Work closely with Business Analysts, Solution Architect, Integration Engineer, Data Governance Lead, and Test Lead
- Prepare technical documentation, deployment scripts, data dictionaries, and handover materials
Requirements
- 4+ years of data engineering experience, with strong hands on experience in Snowflake
- Experience building data pipelines, ELT processes, data models, and analytical data layers
- Strong SQL skills and experience with complex transformations
- Experience working with investment, financial services, accounting, portfolio, or market data is preferred
- Experience with historical data migration, backfill, reconciliation, and data quality validation
- Experience with ETL/ELT tools, orchestration, cloud storage, APIs, and BI/reporting consumption layers
- Familiarity with data governance, lineage, access control, and sensitive financial data
Full Job Posting
Make It Real
- Capgemini Global Insights & Data business line is a market leader in the data, platform, and analytics across all regions and cross many sectors.
- Our offerings include end 2 end data integration to cloud platform, complete suite of AI engineering capabilities and a category of sector based advanced analytics / AI solutions.
Your Role
- Build Snowflake data pipelines, tables, views, procedures, tasks, streams, and transformation logic.
- Implement ingestion, staging, cleansing, transformation, enrichment, and consumption layers.
- Develop source to target mappings for investment, portfolio, accounting, market data, reference data, and operational data sources.
- Build reusable data models for portfolios, holdings, transactions, instruments, valuations, cash, entities, performance, and historical records.
- Support public and private investment data structures, including historical backfill and reconciliation requirements.
- Implement data quality checks, exception handling, audit fields, reconciliation logic, and validation rules.
- Optimize Snowflake performance, including warehouse usage, clustering, query design, data loading, and cost aware engineering.
- Support data security requirements, including role based access, masking, secure views, and data segregation.
- Work closely with Business Analysts, Solution Architect, Integration Engineer, Data Governance Lead, and Test Lead.
- Prepare technical documentation, deployment scripts, data dictionaries, and handover materials.
Your Profile
- 4+ years of data engineering experience, with strong hands on experience in Snowflake.
- Experience building data pipelines, ELT processes, data models, and analytical data layers.
- Strong SQL skills and experience with complex transformations.
- Experience working with investment, financial services, accounting, portfolio, or market data is preferred.
- Experience with historical data migration, backfill, reconciliation, and data quality validation.
- Experience with ETL/ELT tools, orchestration, cloud storage, APIs, and BI/reporting consumption layers.
- Familiarity with data governance, lineage, access control, and sensitive financial data.
Skills
- Snowflake development
- Advanced SQL
- Data modelling and transformation
- Data quality engineering
- Historical data backfill
- Performance tuning
- Investment data awareness
- Documentation and testing discipline
Technical
- Snowflake
- Cloud data platform
- ETL/ELT
- Data integration
- Governance
- Reconciliation
- BI/reporting consumption
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