Lead Analytics Engineer - Data Modeling & Quality

Lead Analytics Engineer focusing on data modeling and data quality, owning the DBT/SQL layer to transform clinical and claims data into trusted datasets with strong data quality ownership and cross-functional collaboration within Arcadia's healthcare analytics platform.

Responsibilities

• Author, review, and maintain DBT models built on Spark/Hudi, spanning ingest through bronze and silver layers.
• Clarify data model concepts for clients by communicating assumptions and limitations via deliberate validation.
• Troubleshoot issues, implement fixes, and create DBT tests to proactively prevent problems.
• Optimize SQL performance for slow-running pipelines and queries.
• Collaborate with Data Engineering on Hudi table design, partition strategies, and incremental processing patterns.
• Triage data quality alerts, distinguishing source-level problems from transform-layer failures.
• Design and maintain volume monitors and data quality monitors (null rates, distribution checks, future-date validations).
• Author and enforce clinical DQ rules (entity volume, field coverage, LOINC coverage, referential integrity) and claims validation rules across silver and gold layers.
• Lead quality reviews for connector promotions, evaluating silver entity coverage, validation pass rates, and bronze-to-silver transformation correctness.
• Own the ticket queue for data quality, attribution, hierarchy, and customer-specific data quality issues, delivering clear, customer-facing findings.
• Guide data quality reviews during connector installation and promotion (UAT/PRD), including claims validation playbooks and null analyses.
• Partner with Data Engineering on root-cause analysis for errors, ingestion anomalies, and silver table issues surfaced by monitoring.
• Coordinate with the Measure Implementation Team when data quality affects quality measure scores.
• Contribute to and enforce data modeling standards across teams.
• Data modeling stack encompasses DBT-Spark, SQL, Claude; warehousing with Redshift, Hudi, and AWS Athena; orchestration via Argo Workflows and Airflow; observability with Grafana and Loki; issue tracking in Jira.
• Maintain robust source control through Git and GitHub with PR-based workflows.
• Work with healthcare data domains including claims (plan, professional, pharmacy), EHR clinical entities, and MPI.

Requirements

• Bachelor's or Master's degree in Computer Science, Statistics, Business, Economics, or a related field.
• Advanced SQL skills with window functions, complex CTEs, multi-step aggregations, and performance tuning on columnar databases.
• Hands-on DBT experience: authoring models, tests, macros, and YAML documentation; familiarity with incremental strategies.
• Healthcare data literacy covering claims data (professional, institutional, pharmacy), clinical data (EHR entities), and quality dimensions (member months, coverage rates, null patterns).
• Data quality mindset with the ability to separate source data issues from transform problems, design systematic validation checks, and communicate findings clearly.
• Clear communicator capable of translating technical insights for clients and non-technical stakeholders.
• Strong analytical judgment and the ability to identify anomalies in data distributions.
• Ability to manage multiple projects concurrently, leveraging AI tooling for organization and efficiency.
• Genuine interest in learning and applying AI tools to improve operations and processes.

Preferred qualifications

• Experience with Spark SQL and the Hudi table format.
• Familiarity with data quality monitoring tools.
• Comfort working in an AI-first environment using Claude to build and verify workflows.
• Exposure to population health analytics concepts such as HEDIS measures, risk adjustment, and value-based care metrics.
• Python scripting for data investigation and automation.
• Experience with Argo Workflows or similar orchestration platforms.
• Healthcare data standards familiarity: ICD-10, CPT, NDC, LOINC, NPI.

Technologies

• DBT-Spark
• SQL
• Claude
• Amazon Redshift
• Apache Hudi
• AWS Athena
• Argo Workflows
• Airflow
• Git
• GitHub
• Grafana
• Loki
• Jira

Benefits

• Collaborate with a talented team tackling complex healthcare data challenges.
• Flexible, fully remote work environment with strong support resources.
• Exposure to senior leadership and strategic initiatives.
• Be at the forefront of AI adoption, leveraging cutting-edge tools to accelerate work and shape team processes.
• Help improve data quality and reliability that inform patient care decisions.
• Join a mission-driven organization transforming the healthcare industry.
• Become part of a diverse, energized Arcadian community aligned with purpose.