PME Data Engineer

King County's Department of Community and Human Services (DCHS) provides equitable opportunities for people to be healthy, happy, and connected to community.

Are you a technical whiz who excels at creating efficient and beautiful scripts, packages, data pipelines and database solutions for use by other data professionals? Do you love helping others understand data systems and how to optimize their design
? Are you excited about being the subject matter expert for large and complex data systems
, and creating processes and documentation for others to build their knowledge? The Performance Measurement and Evaluation (PME) Unit within the Department of Community and Human Services (DCHS) is seeking a savvy Data Engineer to join our team of analytic experts!

DCHS is committed to leveraging data to inform program and investment decisions. We are investing heavily in data systems to collect robust client-level outcome data as well as in data infrastructure to support workflows that combine data across historically siloed service systems. This opens opportunities for more impactful analytics as well as introducing more complex requirements for data management. We are seeking a skilled and collaborative Data Engineer who is interested in working with a wide range of internal partners to expand and optimize our data and data pipeline architecture, as well as optimize data flow and collection for cross functional teams.

This position supports department-wide systems within DCHS.

This position is centrally located within the Performance Measurement and Evaluation (PME) unit of the DCHS Director's Office. PME is composed of a team of dedicated data scientists, engineers, evaluators, and analysts who work with partners within and outside of DCHS to provide insights for data-informed program and policy decisions and test innovative approaches to tackling a variety of system, policy, and service delivery challenges.

This selection process will fill our current vacancy but may also establish a pool of qualified candidates should additional Data Engineer positions open up within the next 6 months.

To be considered minimally qualified applicant must demonstrate a background that provides the knowledge, skills and ability to:

• Consult with partners to define the requirements for collecting, structuring, and organizing data
  ; translate into technical specifications to meet business needs and communicate effectively.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and R.
• Lead data cleaning, management, and validation efforts to ensure the completeness and accuracy of data used to support measurement and evaluation.
• Identify, design, and implement internal process improvements
  : automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Design and build large, complex data sets that meet business requirements.
• Create and maintain architecture diagrams, system documentation, data models, mapping documents, data dictionaries, business rules, data flow diagrams, and other related artifacts.

• Build tools that utilize data pipelines to streamline review and validation processes and provide actionable insights into key performance indicators.
• Develop various metrics and routine reports to support evaluation and measurement, for example those that monitor data submissions. Where relevant, coordinate and align products across different reporting streams.
• Develop dashboards, charts, reports, and presentations that visually represent key findings for non-technical audiences and communicate results in a way that is actionable.
• Respond to other data requests and perform other related duties as assigned.

• Provide consultation to internal partners to assist with technical issues and ensure data obtained through system transactions and other means meets the needs of data analysts and evaluators.
• Provide technical subject matter expertise about data structures, concepts, and interpretation via orientation to data systems, code review, participation in data standards discussions, and counseling on considerations for analytic use and interpretation.
• Monitor and communicate relevant data system changes and implications to technical staff.
• Manage team processes and tools for shared learning, improvement, and documentation of data systems.
• Review data use proposals for technical feasibility and compliance in support of cross-divisional or cross-departmental data collaborations.
• As needed, participate in team, work group, division, department, and cross-department meetings.

• A minimum of five (5) years of work experience, or an equivalent combination of education and work experience in data analytics, computer…