Senior Data Engineer – AWS

We are looking for a skilled Senior Data Engineer with strong AWS expertise to design, develop, and optimize cloud-based data pipelines and solutions. The role involves hands-on development, collaboration with cross-functional teams, and contributing to scalable, high-performance data platforms. The ideal candidate has solid AWS experience, strong programming skills, and an understanding of data engineering best practices.

Responsibilities

Develop and maintain batch and real-time data pipelines on AWS; Implement ETL/ELT solutions using AWS Glue, Spark on EMR, and other AWS services; Assist in workflow orchestration using Apache Airflow (MWAA); Support serverless data processing using AWS Lambda; Participate in designing data warehousing solutions using Amazon Redshift; Design and manage data storage strategies with Amazon S3 and DynamoDB; Apply data governance and access controls using AWS DataZone; Monitor and troubleshoot data platform issues using Amazon CloudWatch; Collaborate with Analytics, BI, Data Science, and Business teams; Write clean, efficient code, and perform peer code reviews; Follow security, compliance, and data governance standards

Requirements

5–7 years of experience in Data Engineering or related roles; 3+ years of hands-on experience designing data solutions on AWS; Proficiency with: 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; Advanced SQL skills with performance tuning expertise; Understanding of data warehousing, data modeling (Star/Snowflake), ETL/ELT best practices; Familiarity with Agile/Scrum delivery environments; Problem-solving and analytical skills

Nice to have

AWS Professional Certification (Solutions Architect / Data Analytics Specialty); Experience with real-time streaming (Kinesis, Kafka); Exposure to data governance and metadata management tools; Knowledge of cost optimization in AWS