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.
Key Responsibilities
- Build, enhance, and maintain scalable ETL/ELT data pipelines and modern data products.
- Work with relational, NoSQL, and graph databases, including Oracle, PostgreSQL, DynamoDB, Elasticsearch, Neptune, and Neo4J.
- Develop batch processing workflows using tools such as AWS EventBridge, 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 DevOps practices using tools such as Maven, Jenkins, AWS CloudFormation 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.
Required Qualifications
- 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, NoSQL, 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, EventBridge, and Step Functions.
- Knowledge of messaging platforms including Kafka, Kinesis, SNS, and SQS.
- Experience using DevOps and CI/CD tools.
- Ability to troubleshoot development, testing, and production issues.
- Strong communication skills and ability to work in distributed Agile teams.
Preferred Qualifications
- AWS Associate, Professional, or Specialty certification.
- Experience with Snowflake data engineering workloads.
- Prior experience in large‑scale, enterprise‑wide data integration environments.