AWS Data Engineer

Overview

Hybrid
$90,000 - $120,000
Full Time
No Travel Required

Skills

Amazon Redshift
Amazon Web Services
Apache Hive
Data Engineering
Python
SQL

Job Details

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, 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 formatdata.
  • 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 manipulatedata.
  • 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.
  • 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.
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