Description

You design, build, and maintain large-scale data pipelines and analytics platforms.

This role is on-site.

Responsibilities

• Design and build ETL/ELT pipelines using AWS-native tools including Glue, Lambda, Step Functions, and EMR.
• Manage large-scale AWS S3 Data Lakes, optimizing storage formats such as Parquet, ORC, and Delta.
• Develop and optimize Amazon Redshift data models, schemas, and high-performance ELT workloads.
• Integrate data from enterprise systems (CRM, ERP) and third-party APIs, supporting real-time ingestion via Kinesis or Kafka.
• Ensure data quality, lineage, and governance across all data workflows.

Required Skills

• 7+ years of hands-on experience in data engineering.
• Expertise with PySpark/Spark or similar distributed processing frameworks.
• Deep knowledge of Amazon Redshift, including performance tuning and workload management.
• Proficiency with AWS services: S3, Glue, Lambda, EMR, IAM, and CloudWatch.
• Strong SQL skills and experience with data modeling (star/snowflake schemas).
• Experience building and managing data lakes and large-scale data pipelines.
• Hands-on experience with streaming technologies such as Kinesis or Kafka.
• Strong understanding of ETL/ELT architecture and data integration patterns.

Preferred Skills

• Experience with real-time data ingestion and processing at scale.
• Background in enterprise system integration (CRM/ERP).

Key Skills

Education

Any Gradute