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.