Description

Altarum Institute


Principal Data Engineer ML Platforms

Altarum | Data & AI Center of Excellence (CoE)
Altarum is building the future of data and AI infrastructure for public health - and were looking for a Principal Data Engineer ML Platforms to help lead the way. In this cornerstone role, you will design, build, and operationalize the modern data and ML platform capabilities that power analytics, evaluation, AI modeling, and interoperability across all Altarum divisions.
If you want to architect impactful systems, enable data science at scale, and help ensure public health and Medicaid programs operate with secure, explainable, and trustworthy AI - this role is for you. What You'll Work On
This role blends deep engineering with applied ML enablement: ML Platform Engineering: modern lakehouse architecture, pipelines, MLOps lifecycle Applied ML enablement: risk scoring, forecasting, Medicaid analytics NLP/Generative AI support: RAG, vectorization, health communicationsCausal ML operationalization: evaluation modeling workflowsResponsible/Trusted AI engineering: model cards, fairness, compliance Your work ensures that Altarums public health and Medicaid programs run on secure, scalable, reusable, and explainable data and AI infrastructure.

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 ARAs 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

• 710+ 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 youre near one of our offices (Arlington, VA; Silver Spring, MD; or Novi, MI), youll 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.

At Altarum, we carefully consider a wide range of compensation factors and rely on market indicators to get it right. Individual compensation packages are based on numerous factors unique to each candidate, including skill set, experience, qualifications, and other job-related reasons. This salary range is not a guarantee of compensation, as the final offer amount will vary based on these factors.
In addition to base salary compensation, Altarum Enterprise employees enjoy the following benefits:
Competitive Medical, Dental and Optical plans Generous Paid Time Off, 8 Company observed holidays plus 3 floating holidays Tuition Assistance 401K Plan (3% employer contribution plus opportunity for gainsharing) Life, AD&D & Disability coverage A flexible work environmentAltarum is a nonprofit organization focused on improving the health of individuals with fewer financial resources and populations disenfranchised by the health care system. We work primarily on behalf of federal and state governments to design and implement solutions that achieve measurable results. We combine our expertise in public health and health care delivery with technology development and implementation, practice transformation, training and technical assistance, quality improvement, data analytics, and applied research and evaluation. Our innovative solutions and proven processes lead to better value and health for all.
Altarum is an equal opportunity employer that provides employment and opportunities to all qualified employees and applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, or any other characteristic protected by applicable law.
$144,771 - $188,036 a year

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