Data Engineer

Peak Finder Consulting Chennai; Chennai District; Hybrid; INR 1,800,000 - 2,400,000; Full time

Job summary

Peak Finder Consulting Chennai is looking for a data engineering professional to design and optimize ELT/ETL pipelines using AWS and Snowflake. The role focuses on building data models, secure ingestion, and monitoring to ensure reliable data availability for BI and product teams.

The candidate will implement quality rules, document lineage, and collaborate across teams to maintain robust data transformations in a Chennai-based environment.

Responsibilities

• Design, build, and optimize ELT/ETL pipelines using AWS (Glue, Lambda, S3) and Snowflake.
• Develop Snowflake data models, including staging, integration, and Gold-layer transformations.
• Create and maintain Snowflake tasks, streams, stored procedures, and pipe-based ingestion.
• Implement data pipeline monitoring, alerting, logging, and auto-recovery mechanisms.
• Tune Snowflake performance through warehouse sizing, caching, clustering, and query optimization.
• Build secure ingestion paths using IAM roles, policies, AWS Secrets Manager, VPC endpoints, etc.
• Collaborate with BI, architecture, and product teams to ensure data availability and quality.
• Develop data quality rules and validation suites for pipeline integrity.
• Document architecture, lineage, mapping, and transformation logic.

Job description

Key Responsibilities

• Design, build, and optimize ELT/ETL pipelines using AWS (Glue, Lambda, S3) and Snowflake.
• Develop Snowflake data models, including staging, integration, and Gold-layer transformations.
• Create and maintain Snowflake tasks, streams, stored procedures, and pipe-based ingestion.
• Implement data pipeline monitoring, alerting, logging, and auto-recovery mechanisms.
• Tune Snowflake performance through warehouse sizing, caching, clustering, and query optimization.
• Build secure ingestion paths using IAM roles, policies, AWS Secrets Manager, VPC endpoints, etc.
• Collaborate with BI, architecture, and product teams to ensure data availability and quality.
• Develop data quality rules and validation suites for pipeline integrity.
• Document architecture, lineage, mapping, and transformation logic.