Job Description

• Develop and maintain scalable batch and real-time data pipelines on AWS
• Build and optimize ELT/ETL pipelines using Snowflake, AWS Glue, and Spark on EMR
• Design and implement Snowflake data warehouse solutions, including schema design, clustering, and performance optimization
• Develop and manage Snowflake data models (Star/Snowflake schemas) for analytics and reporting
• Implement workflow orchestration using Apache Airflow (MWAA)
• Support serverless data processing using AWS Lambda
• Design and manage data lake architectures using Amazon S3 and Snowflake
• Implement data ingestion frameworks for structured and semi-structured data
• Optimize Snowflake query performance, storage usage, and compute costs
• Apply data governance, security, and role-based access controls using AWS DataZone and Snowflake features
• Monitor and troubleshoot data pipelines and platform issues using Amazon CloudWatch and other monitoring tools
• Collaborate with Analytics, BI, Data Science, and Business teams to enable data-driven decision-making
• Write clean, scalable, and efficient code, and participate in peer code reviews and architecture discussions
• Ensure data quality, reliability, and compliance with governance standards

• 6–10+ years of experience in Data Engineering or related roles
• 3+ years of hands-on experience designing and building data platforms on AWS
• Strong experience with Snowflake data warehouse architecture, development, and optimization
• Proficiency with AWS data services, including:
  • AWS Glue
  • Amazon EMR (Spark)
  • AWS Lambda
  • Apache Airflow (MWAA)
  • Amazon EC2
  • Amazon CloudWatch
  • Amazon Redshift
  • Amazon DynamoDB
  • AWS DataZone
  • Amazon S3
• Strong programming skills in Python for data engineering and pipeline development
• Advanced SQL skills with query optimization and performance tuning
• Strong understanding of data warehousing concepts and dimensional modeling (Star/Snowflake)
• Experience building scalable ETL/ELT pipelines and handling large-scale datasets
• Familiarity with Agile/Scrum delivery environments
• Strong problem-solving and analytical skills

• AWS Professional Certification (Solutions Architect / Data Analytics Specialty)
• Snowflake Certification (SnowPro Core or Advanced)
• Experience with real-time streaming technologies (Kinesis, Kafka)
• Exposure to data governance, data catalog, and metadata management tools
• Experience with CI/CD pipelines for data engineering workflows
• Knowledge of cost optimization strategies in AWS and Snowflake