Data Systems and Analytics Engineer

Arbor Research•Ann Arbor, MI

1d•Remote

About The Position

The Data Systems and Analytics Engineer turns raw research and program data into trusted datasets, analyses, and live reporting for federal health research programs. The position spans the full data lifecycle, from ingesting and preparing data to modeling it for analysis and presenting results through dashboards and automated reports. The role combines data engineering skills in SQL, Python or R, ETL, and cloud databases with the ability to communicate information clearly through dashboards, live reports, and publication-ready outputs. The position also provides technical leadership as an architect for data systems and processes, guiding engineers and analysts on design and implementation. It designs and maintains data platforms and workflows, establishes data governance practices and standard operating procedures, leads technical planning, and provides technical direction, code review, and mentoring. The role collaborates with project managers, biostatisticians, data managers, external partners, and technical staff to deliver work on schedule. The role is remote, but the employee must be physically located in Colorado, Washington, D.C., Georgia, Maryland, Michigan, Minnesota, North Carolina, or Virginia. It is an exempt position with a 40-hour workweek, reports to the Program Director, has no supervisory responsibilities, and requires minimal overnight travel (no more than 5%). The salary range is $107,000 to $176,000; compensation depends on market range, geographic pay zone, and individual factors.

Requirements

Bachelor's degree in computer science, data science, statistics, informatics, or a related field.
Five years of progressively more responsible experience in data engineering, programming, or reporting development.
Advanced SQL skills, including data modeling, views, stored procedures, and query optimization in relational databases.
Proficiency in Python or R for data processing and automation, and working knowledge of SAS.
Demonstrated experience developing reports and dashboards, including production dashboards or live reports in Tableau, Power BI, or a custom framework.
Experience building and maintaining ETL pipelines, including data validation and error handling.
Experience with Git version control in a collaborative workflow.
Demonstrated ability to translate user requirements into data models, pipelines, and report designs.
Strong attention to data accuracy and documentation.
Excellent organizational and communication skills.
Demonstrated technical leadership experience, including designing data system architecture and processes, setting technical standards, and mentoring technical staff.

Nice To Haves

Experience with cloud platforms, especially AWS, and an AWS or other cloud certification.
Experience with data orchestration and transformation tools such as Airflow or dbt.
Experience with record linkage or entity resolution across administrative data sources.
Experience with health research data, such as clinical study, registry, biospecimen, or claims data, and with de-identification methods.
Familiarity with government agency data-sharing policies and federal security standards such as FISMA and FedRAMP.
Experience designing accessible Section 508 dashboards and reports.
Experience with survey data or program evaluation data.
Experience supporting federal contracts.
Experience architecting cloud data platforms, such as AWS data lake or warehouse architectures, and an AWS Solutions Architect or Data Engineer certification.
Experience with architecture documentation and modeling tools such as UML, C4, data flow diagrams, and entity-relationship diagrams.
Experience writing and maintaining SOPs in a regulated or quality-managed environment.
Experience with search and indexing tools such as Elasticsearch or OpenSearch.
Experience with AWS security and data services such as KMS, Macie, AWS Backup, Glue, and Athena.
Non-profit experience.

Responsibilities

Design, build, and maintain automated, scheduled, and monitored ETL/ELT pipelines that ingest data from databases, files, APIs, and web platforms into cloud databases and data warehouses, and deliver recurring extracts.
Clean, validate, and transform raw data into analysis-ready datasets, including data dictionaries, codebooks, and documented derivation logic.
Ensure data product accuracy through automated validation checks in pipelines and reports and independent quality control.
Use Git version control and code review, and document systems, pipelines, and dashboards, including archived reproducibility packages, to support maintenance and handoff.
Protect sensitive health data using de-identification and data minimization techniques, and verify de-identification performed by others in accordance with federal security requirements, including access controls, encryption, and audit logging.
Build record linkage and entity resolution processes to join data across sources using deterministic and probabilistic matching.
Harmonize data from multiple sources to common data standards and maintain metadata for search and discovery.
Design relational data models, views, and stored procedures that support analysis and reporting.
Support analysts and biostatisticians with derived variables, matched comparison datasets, and reproducible analysis files.
Present complex metrics and outcomes clearly for leadership, sponsors, and the public, selecting suitable chart types and levels of detail.
Produce publication-ready tables and figures for manuscripts, presentations, and web content.
Design, build, and maintain interactive dashboards and visualizations to track operational and performance metrics such as volumes, turnaround times, trends, and utilization.
Ensure dashboards and reports meet Section 508 and WCAG accessibility standards.
Gather user requirements, prototype layouts, and refine them based on feedback.
Work with project managers, biostatisticians, data managers, and external partners to meet deliverable schedules.
Explain technical approaches and design choices to technical and non-technical audiences.
Use AI tools such as Claude Code for pipeline solutioning and as components of solutions, following organizational guidance and controls.
Serve as technical lead and system architect for data platforms, designing end-to-end architecture across ingestion, storage, processing, security, and delivery layers, including selection of cloud services, databases, and tools.
Design and document data and process workflows and data governance practices to promote consistency, quality, and scalability across projects.
Develop, document, maintain, and update SOPs for data operations, including intake, processing, validation and quality control, de-identification, release, security, and backup and recovery.
Execute data operations according to established SOPs; document adherence, deviations, and corrective actions; and train staff on SOP procedures.
Lead technical planning and estimation, translate project requirements into architecture and implementation plans, and identify technical risks and mitigation strategies.
Provide technical direction, code review, and mentoring to data engineers, programmers, and analysts, and coordinate integrated solutions with software, DevOps, and security staff.
Evaluate emerging technologies and recommend improvements to data infrastructure, automation, and performance.