Description :

About the job :

Role : Senior Snowflake Data Engineer

Exp : 5+ Years

Location : Noida- WFO

Immediate Joiners

We are looking for a Senior Snowflake Data Engineer with 5+ years of hands-on experience to design, build, and optimize scalable, cloud-native data platforms for BFSI clients.

This role demands strong expertise in Snowflake, SQL, and PySpark, along with experience in building production-grade data pipelines, data models, and transformations using modern ELT/ETL frameworks.

You will work closely with architects, analysts, and business stakeholders to deliver reliable, high-performance, analytics-ready data solutions.

Snowflake & Data Warehousing :

- Design, develop, and optimize Snowflake data warehouses, including databases, schemas, stages, and warehouses.

- Build fact and dimension models (Star/Snowflake schemas) to support analytics, reporting, and regulatory use cases.

- Implement performance optimization techniques such as clustering, partitioning, pruning, query profiling, and warehouse sizing.

- Handle large-scale data volumes with cost-efficient Snowflake design.

SQL & Data Transformations :

- Write and optimize complex SQL queries, including CTEs, window functions, subqueries, and incremental logic.

- Develop reusable, scalable transformation logic for business-critical datasets.

- Implement data quality checks, validations, and reconciliation logic using SQL.

PySpark & Data Processing :

- Build and maintain PySpark-based data pipelines for large-scale batch processing.

- Apply Spark best practices such as partitioning, caching, broadcast joins, and file format optimization (Parquet/Delta).

- Troubleshoot and optimize Spark job performance in cloud environments.

ETL / ELT & Orchestration :

- Design and implement end-to-end ETL/ELT pipelines from ingestion to consumption layers.

- Use orchestration tools like Airflow to schedule, monitor, and manage workflows.

- Implement incremental loads, CDC patterns, and failure recovery mechanisms.

DBT & Modern Data Stack :

- Build and maintain DBT models, tests, and documentation for transformation layers.

- Implement data lineage, modular modeling, and version-controlled transformations.

- Collaborate on analytics engineering best practices.

Cloud & Security :

- Work on cloud platforms such as AWS / Azure / GCP, with Snowflake as the core warehouse.

- Ensure data security, governance, and compliance aligned with BFSI standards.

- Collaborate with DevOps teams for CI/CD, monitoring, and production readiness.

Required Skills & Qualifications :

Must-Have :

- 5+ years of experience as a Data Engineer in production environments.

- Strong hands-on experience with Snowflake (data modeling, performance tuning, cost optimization).

- Advanced SQL skills (complex joins, window functions, query optimization).

- Strong PySpark experience for large-scale data processing.

- Solid understanding of data warehousing concepts and ETL/ELT patterns.

- Experience with Airflow or similar orchestration tools.

- Hands-on exposure to DBT for transformations and data modeling.

Good to Have :

- Experience in BFSI / regulated domains.

- Exposure to Cloudera Hadoop, Hive, Impala, or NiFi.

- Experience with CDC, streaming, or near real-time pipelines.

- Familiarity with CI/CD pipelines, Git-based workflows, and cloud monitoring.