AWS Cloud Data Engineer

Junior Data Engineer (2 to 4 years experience)

Position Overview

We are seeking a highly skilled AWS Cloud Data Engineer to design, build, and maintain scalable data pipelines and infrastructure on AWS. The ideal candidate will have hands-on experience with cloud-native services, strong data engineering capabilities, and expertise in supporting enterprise-level data ingestion, transformation, and management initiatives.

Key Responsibilities

. Design, develop, and maintain data pipelines and ETL/ELT workflows using AWS services.

. Build and optimize data lakes and data warehouses on AWS (e.g., S3, Redshift, Snowflake, Databricks).

. Implement data ingestion from multiple structured and unstructured sources.

. Develop and deploy scalable data processing solutions using AWS Lambda, Glue, EMR, Kinesis, Step Functions, and Terraform.

. Ensure data quality, governance, and security in compliance with organizational and regulatory standards.

. Collaborate with data scientists, analysts, and business stakeholders to enable analytics and AI/ML initiatives.

. Monitor, troubleshoot, and optimize data infrastructure performance and costs.

Required Skills & Qualifications

. Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.

. 2 to 4 years of experience in Data Engineering with strong exposure to AWS Cloud.

. Strong hands-on expertise with AWS services such as S3, Glue, Redshift, Lambda, IAM, CloudFormation/Terraform.

. Experience with data pipeline orchestration (Airflow, Step Functions, or similar).

. Proficiency in Python, SQL, and PySpark.

. Strong knowledge of data warehousing, data lakes, and data management practices.

. Familiarity with Snowflake, Databricks, or similar platforms (preferred).

. Strong understanding of DevOps practices, CI/CD pipelines, and cloud infrastructure.

. Excellent problem-solving and communication skills.