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Data Ops Engineer
| Company | Expression Networks |
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| Location | Annapolis, MD, USA |
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| Salary | $100000 – $160000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Associate’s |
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| Experience Level | Senior, Expert or higher |
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Requirements
- Top Secret with capability to obtain a CI Poly
- Security+ certification (or willingness to get certified within the first month)
- Associates degree or higher in engineering, computer science, or related field and 5+ years of experience as a DevOps/Cloud/Software engineer -OR- 8+ years of experience as a DevOps/Cloud/Software engineer
- Proficiency in programming languages such as Python, Java, or Scala.
- Strong experience with relational databases (e.g., PostgreSQL, MySQL) and big data technologies (e.g., Hadoop, Spark).
- Experienced with Elasticsearch and Cloud Search.
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with data pipeline orchestration tools (e.g., Airflow, Luigi) and workflow automation tools (e.g., Jenkins, GitLab CI/CD).
- Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) is a plus.
- Data pipeline management
- Proven experience maintaining production systems for external customers
- Experience working with Open Source Technologies such as Red Hat (OpenShift) and Linux/Unix
- Engaging with Data engineers in troubleshooting issues
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
Responsibilities
- Design, implement, and maintain robust data infrastructure, including databases, data warehouses, and data lakes, to support our rapidly expanding data landscape.
- Develop, deploy, and test ETL pipelines for extracting, transforming, and loading data from various sources.
- Collaborate with data scientists and data engineers to integrate and test machine learning models within our data systems.
- Implement cutting-edge automation and orchestration tools to streamline data operations, minimize manual processes, and boost efficiency.
- Continuously assess and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness.
- Establish proactive monitoring and alerting mechanisms to detect and address potential issues in real time.
- Work closely with cross-functional teams—including data scientists, analysts, and software engineers—to understand evolving data requirements.
- Create comprehensive documentation of data infrastructure, pipelines, and processes. Help promote a culture of continuous improvement by sharing knowledge and best practices within the team.
Preferred Qualifications
- Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) is a plus.
