Principal Data Engineer – ML Platforms

Altarum | Data & AI Center of Excellence (CoE)

What You'll Work On

What You'll Do

• Platform Architecture & Delivery
• Design and operate modern, cloud-agnostic lakehouse architecture using object storage, SQL/ELT engines, and dbt.
• Build CI/CD pipelines for data, dbt, and model delivery (GitHub Actions, GitLab, Azure DevOps).
• Implement MLOps systems: MLflow (or equivalent), feature stores, model registry, drift detection, automated testing.
• Engineer solutions in AWS and AWS GovCloud today, with portability to Azure Gov or GCP.
• Use Infrastructure-as-Code (Terraform, CloudFormation, Bicep) to automate secure deployments.

Pipelines & Interoperability

• Build scalable ingestion and normalization pipelines for healthcare and public health datasets, including:
• FHIR R4 / US Core (strongly preferred)
• HL7 v2 (strongly preferred)
• Medicaid/Medicare claims & encounters (strongly preferred)
• SDOH & geospatial data (preferred)
• Survey, mixed-methods, and qualitative data
• Create reusable connectors, dbt packages, and data contracts for cross-division use.
• Publish clean, conformed, metrics-ready tables for Analytics Engineering and BI teams.
• Support Population Health in turning evaluation and statistical models into pipelines.

Data Quality, Reliability & Cost Management

• Define SLOs and alerting; instrument lineage & metadata; ensure ≥95% of data tests pass.
• Perform performance and cost tuning (partitioning, storage tiers, autoscaling) with guardrails and dashboards.

Applied ML Enablement

• Build production-grade pipelines for risk prediction, forecasting, cost/utilization models, and burden estimation.
• Develop ML-ready feature engineering workflows and support time-series/outbreak detection models.
• Integrate ML assets into standardized deployment workflows.

Generative AI Enablement

• Build ingestion and vectorization pipelines for surveys, interviews, and unstructured text.
• Support RAG systems for synthesis, evaluation, and public health guidance.
• Enable Palladian Partners with secure, controlled-generation environments.

Causal ML & Evaluation Engineering

• Translate R/Stata/SAS evaluation code into reusable pipelines.
• Build templates for causal inference workflows (DID, AIPW, CEM, synthetic controls).
• Support operationalization of ARA’s applied research methods at scale.

Responsible AI, Security & Compliance

• Implement Model Card Protocol (MCP) and fairness/explainability tooling (SHAP, LIME).
• Ensure compliance with HIPAA, 42 CFR Part 2, IRB/DUA constraints, and NIST AI RMF standards.
• Enforce privacy-by-design: tokenization, encryption, least-privilege IAM, and VPC isolation.

Reuse, Shared-Services, and Enablement

• Develop runbooks, architecture diagrams, repo templates, and accelerator code.
• Pair with data scientists, analysts, and SMEs to build organizational capability.
• Provide technical guidance for proposals and client engagements.
Your First 90 Days - You will make a meaningful impact fast. Expected outcomes include:
• Platform skeleton operational: repo templates, CI/CD, dbt project, MLflow registry, tests.
• Two pipelines in production (e.g., FHIR → analytics and claims normalization).
• One end-to-end CoE lighthouse MVP delivered (ingestion → model → metrics → BI).
• Completed playbooks for GovCloud deployment, identity/secrets, rollback, and cost control.

Success Metrics (KPIs)

• Pipeline reliability meeting SLA/SLO targets.
• ≥95% data tests passing across pipelines.
• MVP dataset onboarding ≤ 4 weeks.
• Reuse of platform assets across ≥3 divisions.
• Cost optimization and budget adherence.

What You'll Bring

• 7–10+ years in data engineering, ML platform engineering, or cloud data architecture.
• Expert in Python, SQL, dbt, and orchestration tools (Airflow, Glue, Step Functions).
• Deep experience with AWS + AWS GovCloud.
• CI/CD and IaC experience (Terraform, CloudFormation).
• Familiarity with MLOps tools (MLflow, Sagemaker, Azure ML, Vertex AI).
• Ability to operate in regulated environments (HIPAA, 42 CFR Part 2, IRB).

Preferred:

• Experience with FHIR, HL7, Medicaid/Medicare claims, and/or SDOH datasets.
• Databricks, Snowflake, Redshift, Synapse.
• Event streaming (Kafka, Kinesis, Event Hubs).
• Feature store experience.
• Observability tooling (Grafana, Prometheus, OpenTelemetry).
• Experience optimizing BI datasets for Power BI.

Logistical Requirements

• At this time, we will only accept candidates who are presently eligible to work in the United States and will not require sponsorship.
• Our organization requires that all work, for the duration of your employment, must be completed in the continental U.S. unless required by contract.
• If you’re near one of our offices (Arlington, VA; Silver Spring, MD; or Novi, MI), you’ll join us in person one day every other month (6 times per year) for a fun, purpose-driven Collaboration Day. These days are filled with creative energy, meaningful connection, and team brainstorming!
• Must be able to work during Eastern Time unless approved by your manager.
• Employees working remotely must have a dedicated, ergonomically appropriate workspace free from distractions with a mobile device that allows for productive and efficient conduct of business.