Job Summary

We are seeking a highly experienced Data Engineer (6-12 years) with expertise in Snowflake, DBT, Apache Airflow, and StreamSets, and strong hands-on experience in designing enterprise-grade ETL/ELT, data migration, and multi-source ingestion frameworks within the Life Sciences domain.

Key Responsibilities

- Snowflake Architecture & Enterprise Data Platform Design

· Lead architecture and implementation of scalable Snowflake data platforms:

o Multi-layered architecture (Landing → Raw → Staging → Curated → Data Marts)

· Develop secure cross-account data sharing strategies.

· Implement:

o Snowpipe for automated ingestion o Streams & Tasks for CDC-based incremental processing o Time Travel & Zero-copy cloning for environment management

· Implement data masking, row-level security, and RBAC frameworks.

· Optimize storage, partitioning (micro-partition pruning), and query performance.

- Data Migration & Modernization

· Participate in end-to-end data migration initiatives including:

o Legacy data warehouse (Teradata, Oracle, SQL Server, Netezza) to Snowflake o On-prem to cloud modernization programs o Source system analysis and profiling o Data quality assessment and remediation planning o Schema conversion and transformation mapping o Incremental migration strategies o Parallel-run validation strategies

· Perform reconciliation and data validation between legacy and target systems.





· Develop automated validation scripts using SQL and DBT tests.

· Support cutover planning and production readiness.

- Data Ingestion & Multi-Source Integration

Design and implement ingestion frameworks for structured, semi-structured, and unstructured data from multiple enterprise systems:

Structured Sources

· Oracle, SQL Server, SAP, PostgreSQL

· Clinical systems (EDC, CDMS, CTMS)

· Regulatory systems (RIM)

· Commercial systems (CRM, ERP)

Semi-Structured Sources

· JSON, XML, Avro files

· API responses

· External vendor feeds

- DBT – Enterprise Transformation Framework

· Design/ Develop DBT transformation layers:

o Staging models o Intermediate models o Data marts

· Implement:

o Incremental models o Snapshot strategies for historical tracking o Surrogate key management

· Develop custom macros and reusable transformation components.

· Optimize DBT models specifically for Snowflake compute efficiency.

Required Qualifications

· 6-12+ years of experience in Data Engineering and Enterprise Data Platforms.

· 4–6+ years hands-on Snowflake implementation experience.

· Robust experience in:

o Large-scale data migration programs o Multi-source data ingestion frameworks o DBT advanced transformation design o Apache Airflow orchestration o StreamSets ingestion pipelines

· Advanced SQL expertise.

· Experience in Life Sciences domain projects.

· Cloud platform experience (AWS/Azure/GCP).

📌 Snowflake DBT(Neha) (Bengaluru)
🏢 TalentOla
📍 Bengaluru