GE AerospaceRemote
Sr. Data Engineer
United States of America
Full Time
3 weeks ago
$93,000 - $124,000 USD
No H1B
Key skills
PythonBash scriptingDockerAWS LambdaAWS CloudTrailAWS X-RayAWS CloudWatchAWS S3AWS IAMPrometheusGrafanaDatadogFluentBitELK stackOpenSearchAirflowAWS GlueAWS Step FunctionsOpenTelemetryEnd-to-End lineage strategyChange Data Capture toolingAWS DMSDebeziumSQLElasticsearchAMI creationCI/CD pipelinesInfrastructure as CodeTerraformCloudFormationBashAIMachine LearningReactVueNode.jsAWSKubernetesLambdaS3IAMCloudWatchGlueELK StackCI/CD
About this role
GE Aerospace is a leader in aerospace technology, and they are seeking a Sr. Data Engineer to enhance their EDAS platform. The role involves building automation solutions, ensuring platform reliability, and collaborating with teams to optimize workflows and performance.
Responsibilities:
- 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
Requirements:
- 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, CloudTrail, X-Ray, CloudWatch, S3, IAM)
- Observability Tools: Prometheus, Grafana, Datadog, FluentBit, ELK stack, OpenSearch
- Data Pipelines: Airflow, Glue, Step Functions
- Standards: OpenTelemetry, E2E lineage strategy, CDC tooling (AWS DMS, Debezium)
- Databases: SQL, Elasticsearch/OpenSearch stacks
- Infrastructure: AMI creation, deployment, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation)
- Legal authorization to work in the U.S. is required
- Web application stacks (Node.js, Vue, React)
- Security/compliance observability integration
- Custom connectors/APIs for observability tools
- OpenMetadata experience
- Machine learning or AI-driven automation techniques
- Kubernetes for container orchestration