Snowflake Data Engineer

4-8 Years Delhi-NCR, Bengaluru, Jaipur, Pune

• Snowflake
• Data Engineer
• SQL
• Data Modeling

Snowflake Data Engineer

Snowflake Investment Data Platform Implementation

Role Purpose

The Snowflake Data Engineer will design, build, test, and optimize data pipelines, data models, and transformation logic within Snowflake to support investment data consolidation, reporting, analytics, governance, and historical data backfill.

Domain Focus

Investment data, public/private assets, historical backfill, portfolio reporting, data quality, and controlled delivery.

Technology Focus

Snowflake, cloud data platform, ETL/ELT, data integration, governance, reconciliation, and BI/reporting consumption.

Delivery Context

Sensitive financial data environment; structured phased delivery with formal governance, 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-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.

Required Experience

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.

Required Skills

Snowflake development

Advanced SQL

Data modelling and transformation

Data-quality engineering

Historical data backfill

Performance tuning

Investment data awareness

Documentation and testing discipline

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