Description

Job Summary:
We are seeking a highly experienced AWS Data Engineer with 15+ years of experience in building and managing large-scale data pipelines and cloud-based data platforms. The ideal candidate will have deep expertise in AWS Glue, Snowflake, Python, and AWS Lambda, and will be responsible for designing, developing, and optimizing ETL/ELT workflows that support enterprise-level data initiatives.

Key Responsibilities:

• Design, build, and maintain scalable ETL/ELT pipelines using AWS Glue and related AWS services
• Develop and optimize data models and data warehousing solutions on Snowflake
• Write efficient, reusable, and reliable Python code for data transformation and automation
• Build and manage serverless data processing workflows using AWS Lambda
• Integrate data from multiple sources (structured/unstructured) into centralized data platforms
• Monitor, troubleshoot, and optimize data pipeline performance and cost
• Implement data quality checks, validation, and error-handling frameworks
• Collaborate with data architects, analysts, and business stakeholders to understand data requirements
• Ensure data security, governance, and compliance best practices across AWS environments
• Document data flows, pipeline architecture, and technical specifications

Required Skills:

• 15+ years of overall IT experience, with strong focus on data engineering
• Hands-on expertise with AWS Glue (jobs, crawlers, workflows, Glue Studio)
• Strong experience with Snowflake (data modeling, performance tuning, SnowSQL, Snowpipe)
• Advanced proficiency in Python for scripting, automation, and data processing (Pandas, PySpark a plus)
• Solid experience with AWS Lambda for serverless/event-driven architectures
• Experience with other AWS services: S3, Redshift, Athena, Step Functions, CloudWatch, IAM
• Strong SQL skills for data querying, transformation, and optimization
• Experience with orchestration tools (Airflow, AWS Step Functions, or similar)
• Understanding of data warehousing concepts, dimensional modeling, and data lake architecture
• Experience with CI/CD pipelines for data engineering workflows (Git, Jenkins, CodePipeline)

Nice to Have:

• Experience with real-time data streaming (Kinesis, Kafka)
• Knowledge of Terraform/CloudFormation for infrastructure as code
• Exposure to data governance and cataloging tools (AWS Glue Data Catalog, Collibra)

Key Skills

Education

Any Graduate