Role: AWS Data Engineer
Location: Hybrid
- Newark, NJ office
- 1 – 2 / Days per Week
We are seeking a skilled AWS Data Engineer who has experience working with Python, SQL, Glue, RedShift, Lambda, Airflow, Medallion Architecture, and Step Functions.
Responsibilities:
• Design, build, and optimize ETLs using Python, SQL, Lambda, Glue, RedShift, Airflow, Step Functions and other AWS services.
• Develop and maintain ETL workflows using Python, SQL, and AWS-native tools.
• Create SQL queries to segment, manipulate, and format data.
• Provide Run/DevOps support for data services, ensuring high availability and performance.
• Collaborate with data scientists, business analysts, SAP functional SMEs and other stakeholders to resolve data-related issues and improve system reliability.
• Implement batch job scheduling and manage data dependencies using tools like Airflow or Step Functions.
• Maintain documentation for data flows, incident resolution, and operational procedures.
• Participate in on-call rotations and incident response for production systems.
• Build automations to ingest, transfer, move, upload, and manipulate data.
• Build or maintain data ingestion pipelines that move data from source systems into Snowflake.
• Create and manage data models to ensure data integrity and facilitate efficient data analysis.
• Implement and maintain data security and compliance measures, including access controls, encryption, and data masking.
• Ensure data quality, accuracy, and consistency through data validation, cleansing, and monitoring.
Requirements:
• Bachelor’s degree in Computer Science, Engineering, or related field.
• 3–5 years of experience in data engineering or production support roles.
• Strong proficiency in AWS services: S3, Glue, Lambda, Redshift, DMS, CloudWatch.
• Good understanding of Medallion architecture
• Solid programming skills in Python and SQL.
• Experience with DevOps tools: GitLab, Jenkins, Bitbucket, Maven.
• Familiarity with data processing frameworks: Spark, Hive, Kafka.
• Must have experience with Airflow and Step Functions.
• Advanced SQL query development proficiency
• Understanding of data modelling principles and techniques.
• Knowledge of data security best practices and compliance requirements.
