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CodaMetrix

AI platform automates clinical coding

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeBoston, MA, USA$130k - $170k /yrHybrid

About the Job

Requirements

  • A degree in Computer Science or a related field (Bachelor's, Master's, or Ph.D.), or an equivalent combination of education and demonstrable professional experience.
  • 3–5+ years of data engineering experience with progressive responsibility.
  • 3–5+ years of hands-on experience with the Databricks platform, including Unity Catalog, Delta Lake, Structured Streaming, Spark SQL, cluster management, and platform administration.
  • Expert proficiency in PySpark and Python, with working knowledge of Scala.
  • Expert experience with Terraform for infrastructure as code, including state management, modular structures, multi-environment deployments, and YAML-driven configuration.
  • Expert experience with Apache Kafka or AWS MSK, including streaming ingestion, SASL/IAM authentication, topic management, and cluster migrations.
  • Deep understanding of medallion/lakehouse architecture patterns, including bronze/silver/gold, SCD2, materialized views, and slowly changing dimensions.
  • Proven track record building and maintaining CI/CD pipelines, including Jenkins and GitHub Actions, for data platform deployments.
  • Expert SQL skills, including complex CTEs, window functions, and performance optimization of large-scale queries across petabyte-scale datasets.
  • Strong AWS experience, including S3, IAM, Secrets Manager, VPC/Private Link, and cross-region replication.
  • Demonstrated ability to operate in a HIPAA-regulated environment with PHI handling requirements.
  • Experience with disaster recovery architecture, including cross-region replication, failover procedures, and read-only replicas.
  • Experience using AI tools such as Claude, Gemini, or Codex and agentic workflows to augment design, development, and testing processes.

Responsibilities

  • Contribute to the vision, architecture, and roadmap for the data platform, ensuring scalability, reliability, regulatory alignment, and operational excellence; participate in key technology decisions, disaster recovery design, architecture reviews, and data engineering standards across teams.
  • Design, build, and maintain scalable streaming and batch data platforms in Databricks using PySpark, Unity Catalog, Delta Lake, and Structured Streaming.
  • Own Terraform-based infrastructure across environments, including jobs, catalogs, schemas, permissions, compute policies, volumes, and external locations.
  • Build Jenkins CI/CD workflows for automated testing, tagging, and deployments, while optimizing training pipelines, materialized views, retention policies, and production performance.
  • Implement and evolve least-privilege access controls across Databricks using Unity Catalog grants, YAML-driven group policies, and schema-level restrictions.
  • Ensure HIPAA and SOC 2 compliance through PHI masking, audit logging, environment-level data segmentation, user provisioning, compute policies, and cost attribution.
  • Drive platform cost reduction through compute policy tuning, serverless optimization, reserved pools, materialized view improvements, and remediation of underutilized resources.
  • Monitor Databricks and AWS spend using tools such as CloudZero and AWS Cost Explorer; own cost attribution and budgeting, resolve production incidents, and maintain runbooks to ensure platform SLAs for uptime and performance.
  • Enable ML, BI, Analytics, DevOps, customer success, and implementation teams with training data pipelines, model-ready datasets, feature store architecture, optimized views, dashboards, Tableau refreshes, infrastructure changes, and tenant onboarding.
  • Mentor engineers through code and design reviews, establish quality standards, and serve as a subject matter expert for data platform engineering across the organization.

Desired Qualifications

  • Prior experience working with healthcare data, such as medical claims, electronic health records (EHR), or billing code systems (ICD-10, CPT).
  • Familiarity with healthcare data standards such as HL7 or FHIR.

About the Company

CodaMetrix

AI platform automates clinical coding

CodaMetrix provides an AI-powered medical coding platform for healthcare providers to translate clinical information into accurate codes, reducing administrative work and supporting revenue cycle processes. The system autonomously codes up to 70% of cases, reducing manual coding by 60-70% and speeding turnaround, while continuously learning from more data to improve coding across multiple specialties. It differentiates itself from rule-based NLP and existing CAC by offering autonomous, multi-specialty coding with ongoing learning to cut denials and coding costs at scale. The goal is to ease provider administrative burden, accelerate coding, lower costs, and improve revenue cycle outcomes through scalable AI-assisted medical coding.

Company size
51-200
Company stage
Series B
Total funding
$95M
Headquarters
Boston, MA
Founded
2018

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