AWS Snowflake Data Engineer

AWSSnowflake Data Engineer

Location: Pune / Nagpur (Work From Office)

Experience: 58 Years

Role Overview

We are looking for a Senior AWS Data Engineer with strong Snowflake expertise to design, build, and optimize scalable, secure, and high-performance data platforms.

You will own end-to-end cloud data pipelines, work with diverse data sources, and deliver analytics-ready datasets by collaborating closely with data science, analytics, and business teams.

Key Responsibilities

• Design and build scalable ETL/ELT pipelines on AWS using Glue, Lambda, Step Functions, EventBridge, loading data into Snowflake and S3 data lakes
• Ingest and process data from multiple sources:
• S3, SFTP (AWS Transfer Family)
• REST / SOAP / FAST APIs
• Relational databases
• Real-time streams (Kinesis)
• Third-party SaaS platforms
• Architect and manage Snowflake-centric data platforms, including:
• Staging Warehouse Consumption layers
• Virtual warehouses, zero-copy cloning, time travel, streams & tasks
• Optimize Snowflake performance and cost, including clustering, materialized views, search optimization, query profiling, auto-suspend, and resource monitors
• Optimize Amazon Redshift performance and cost; manage S3 data lake zones (raw, refined, curated)
• Ensure data quality, reliability, lineage, and consistency using validation frameworks, idempotent pipelines, and automated testing
• Orchestrate event-driven workflows using Step Functions and EventBridge
• Implement CI/CD pipelines using CodePipeline and/or GitHub Actions with Git version control
• Design and enforce enterprise-grade security:
• VPC isolation, IAM least-privilege policies
• KMS encryption, Secrets Manager, PrivateLink
• CloudTrail and GuardDuty for auditing and monitoring
• Set up monitoring, alerting, and logging using CloudWatch, Snowsight, and automated recovery mechanisms
• Manage AWS Glue Data Catalog and Lake Formation for metadata, governance, and access control
• Create technical documentation, architecture diagrams, and runbooks
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable data solutions
• Continuously identify and resolve performance bottlenecks, cost inefficiencies, and technical debt

Required Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, or related field
• 58 years of hands-on Data Engineering experience, with 4+ years on AWS
• Strong expertise in Snowflake, including:
• Architecture, Snowpipe, Streams & Tasks
• Snowpark
• Performance and cost optimization
• Expert-level proficiency in Python and SQL
• Extensive experience with AWS data services, including:
• Glue (Crawlers, Jobs, Spark)
• Lambda, Step Functions, EventBridge
• S3, Kinesis, API Gateway, Athena
• Redshift, Lake Formation
• SnowflakeAWS integrations
• Solid understanding of cloud security and compliance, including IAM, VPC, KMS, Secrets Manager, Transfer Family, CloudTrail, and GuardDuty
• Proven experience building and supporting production-grade data pipelines handling large-scale (TB+) data with strict SLAs

Preferred Qualifications

• AWS Certified Data Engineer (Associate/Professional) or equivalent certifications
• SnowPro Associate or Professional certification
• Experience with Snowpark, dbt, Airflow (MWAA)
• Hands-on experience with real-time analytics and streaming (Kinesis, Lambda, MSK)
• Familiarity with big data ecosystems (Spark, EMR) and cost optimization strategies (Savings Plans, Reserved Instances, S3 Intelligent-Tiering)
• Strong communication skills with the ability to mentor junior engineers