Lead Data Engineer
|Federal Hill Consulting is looking for a Data Engineer in Washington, DC. |
Summary of Position:
- Developing and managing data processes to ensure that data is available and usable
- Creation and automation of data pipelines and platforms
- Managing and monitoring data quality via automated testing frameworks (Data Driven Testing, TDD, etc.)
- Working closely with Architects, Data Scientists, and DevOps to design, build, test, deliver, and maintain sustainable and highly scalable data solutions
- Researching data acquisition and evaluating suitability
- Integration of data management solutions into client environment
- Actively managing risks to data and ensuring there is a data recovery plan
- 7+ years of relevant professional work experience.
- Minimum of 5 years of hands on development experience in a technical role.
- Explaining technical concepts in a business value context.
- Technically savvy, entrepreneurial spirit who thrives in environments that reward self-initiative and resourcefulness.
- Experience and expertise in the following:
- Creating robust and extensible data pipelines for production systems
- Use of cloud platforms, preferably AWS
- Creating secure, performant, and well-modeled data stores
- Common analytical platform architectural patterns (Star Schema, data integration patterns, ABAC, data quality frameworks etc.)
- Data lake design patterns and technology options (schema on read, metadata capture, search framework)
- Use of scripting languages, preferably Python
- Source code version control management using git
- Experience using NoSQL (e.g. Mongo, Neo4j) databases and data structures.
- Excellent communication skills to be able to interact directly with non-technical client stakeholders and act in a business-to-technical translation role.
- Experience working in an onsite client technical consulting environment preferred
- Experience working within Agile Frameworks, such as Scrum or Kanban
We are an equal opportunity employer and value diversity. All employment is decided on the basis of qualifications, merit and business need.