Sr. Data Engineer
Listed on 2026-01-29
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IT/Tech
Data Engineer, Cloud Computing, Data Security, Cybersecurity
Job Description Summary
As the Sr. Data Engineer, you will play a critical role in building and architecting automation and observability for the EDAS platform, with a particular focus on the data consumption side in the near term. You will be responsible for emphasizing automating workflows, ensuring platform reliability by developing data‑driven observability tools and collaborating with teams to enhance efficiency and performance. The platform to automate & observe includes Redshift, Spotfire and triggers, Dataiku project flows, and Talend.
The role focuses on designing and implementing automation solutions to streamline workflows, enhance efficiency, and ensure platform reliability. It involves building observability frameworks for real‑time monitoring, logging, and alerting, optimizing data pipelines for scalability, and ensuring compliance with data governance and security standards.
Job Description In this role you will:- Build and maintain observability frameworks to monitor the health, performance, and reliability of data and analytic platforms.
- Implement tools for real‑time monitoring, logging, and alerting to ensure proactive issue detection and resolution.
- Analyze system metrics and logs to identify trends, anomalies, and areas for improvement.
- Design and implement intelligent automation solutions to streamline data and analytic processing workflows and platform operations.
- Develop scripts, tools, and frameworks to automate repetitive tasks and improve system efficiency.
- Collaborate with cross‑functional teams to identify automation opportunities and implement solutions.
- Ensure high availability and fault tolerance of the platform through robust monitoring and automation strategies.
- Bachelor’s degree from accredited university or college with minimum of 2 years of professional experience OR associate's degree with minimum of 5 years of professional experience OR High School Diploma with minimum of 7 years of professional experience.
- Programming: Python, Bash scripting.
- Containerization: Docker.
- Cloud Services: AWS (Lambda, Cloud Trail, X‑Ray, Cloud Watch, S3, IAM).
- Observability Tools: Prometheus, Grafana, Datadog, Fluent Bit, ELK stack, Open Search.
- Data Pipelines: Airflow, Glue, Step Functions.
- Standards: Open Telemetry, E2E lineage strategy, CDC tooling (AWS DMS, Debezium).
- Databases: SQL, Elasticsearch/Open Search stacks.
- Infrastructure: AMI creation, deployment, CI/CD pipelines, Infrastructure as Code (Terraform/Cloud Formation).
- Note:
Military experience is equivalent to professional experience.
Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.
The base pay range for this position is $93,000 - $155,000. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan. This posting is expected to close on August 31, 2025.
Healthcare benefits include medical, dental, vision, and prescription drug coverage; access to a Health Coach, a 24/7 nurse‑based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Retirement Savings Plan, a tax‑advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and planning consultants.
Other benefits include tuition assistance, adoption assistance, paid parental leave, disability insurance, life insurance, and paid time‑off for vacation or illness.
- Web application stacks (Node.js, Vue, React).
- Security/compliance observability integration.
- Custom connectors/APIs for observability tools.
- Open Metadata experience.
- Machine learning or AI‑driven automation techniques.
- Kubernetes for container orchestration.
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