Data Engineer

The Data Engineer will design, develop, and maintain scalable, resilient, and cost-efficient data products across cloud and on-premises environments.

This role requires expertise in modern data platforms, strong programming skills, and the ability to build reliable data pipelines that support enterprise-wide data integration and analytics initiatives.

The engineer will collaborate across teams to support a platform modernization journey and deliver high-value operational data solutions.

• Build, enhance, and maintain scalable ETL/ELT data pipelines and modern data products.
• Work with relational, No
  
  SQL, and graph databases, including Oracle, Postgre
  
  SQL, Dynamo
  
  DB, Elasticsearch, Neptune, and Neo4J.
• Develop batch processing workflows using tools such as AWS Event Bridge, Step Functions, Lambda, S3, EC2, ECS/EKS, or similar technologies.
• Orchestrate workflows and schedules using Control‑M, Airflow, Argo, cron, or equivalent tools.
• Write, optimize, and debug complex SQL queries, PL/SQL procedures, and data transformation logic.
• Develop data engineering solutions using programming and scripting languages such as Python, Java, and Unix shell scripting.
• Build and operate scalable data solutions on cloud platforms, preferably AWS and Snowflake.
• Utilize messaging and streaming platforms such as Kafka, Kinesis, SNS, and SQS.
• Implement CI/CD pipelines and Dev Ops practices using tools such as Maven, Jenkins, AWS Cloud Formation Templates, uDeploy, Stash, and Ansible.
• Manage testing, deployment, and release processes across environments.
• Diagnose and resolve issues during development, testing, and production.
• Collaborate effectively with global, distributed teams in an Agile environment.
• Communicate clearly and effectively through verbal and written channels.

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related technology field.
• Strong ability to learn and implement new technologies in a fast‑paced environment.
• Experience designing and building scalable, resilient, and cost‑effective data engineering solutions (preferably on AWS and Snowflake).
• Hands‑on experience with relational, No
  
  SQL, and graph databases.
• Strong understanding of data modeling and data integration patterns.
• Experience developing batch processes and data pipelines.
• Proficiency in SQL, PL/SQL, and debugging complex data logic.
• Experience with Unix scripting, Python, and/or Java.
• Experience with data orchestration tools and job schedulers.
• Knowledge of cloud services such as Lambda, S3, ECS/EKS, Event Bridge, and Step Functions.
• Knowledge of messaging platforms including Kafka, Kinesis, SNS, and SQS.
• Experience using Dev Ops and CI/CD tools.
• Ability to troubleshoot development, testing, and production issues.
• Strong communication skills and ability to work in distributed Agile teams.

• AWS Associate, Professional, or Specialty certification.
• Experience with Snowflake data engineering workloads.
• Prior experience in large‑scale, enterprise‑wide data integration environments.