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Analytics Engineer, Life Sciences Delivery Operations

3 weeks ago
Anywhere
Full-time
Senior
Analytics Engineer
Data Science and Analytics
Agile Apache Spark AWS CI/CD Confluence dbt Git GitHub JIRA Kubernetes Microservices Python Snowflake SQL
Apply Now
Arcadia

Arcadia

Arcadia provides a healthcare data platform that enables organizations to unify diverse data sources, derive actionable insights through analytics, and enhance patient outcomes by delivering high-quality care experiences.

IT Services
251-1K
Founded 2002
$154M raised
View All Jobs 12

Description

  • Author and maintain dbt models and PySpark transformation jobs, replacing ad hoc Snowflake scripts with governed, version-controlled code.
  • Design and implement delivery endpoint configurations for customers, delivery targets, cadence, cohort filters, and refresh methods.
  • Write production-grade Python, PySpark, and SQL for data transformation, validation automation, and pipeline components.
  • Configure and maintain AWS S3 delivery paths, Apache Iceberg structures, and file staging patterns for partner deliveries.
  • Build and extend Argo Workflows orchestration to automate monthly delivery execution and remove manual runbooks.
  • Implement HIPAA de-identification compliance rules and coordinate certification updates when data elements or rules change.
  • Coordinate monthly RWD deliveries, including job execution, manifest generation, tokenization workflows, and QC.
  • Own the channel partner data inquiry queue, triage issues, perform root cause analysis, and communicate findings clearly.
  • Define and monitor delivery quality metrics, acceptance criteria, and UAT for pipeline and delivery changes.
  • Maintain query libraries, data dictionaries, and documentation in Confluence, Jira, and GitHub.

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field, or equivalent professional experience.
  • 5+ years of hands-on data engineering experience and 5+ years of direct experience with life sciences RWD data; overlap is acceptable if depth is strong in both.
  • Production-grade SQL proficiency in Snowflake or a comparable columnar warehouse.
  • Hands-on Python and/or PySpark experience writing and debugging production Spark jobs.
  • dbt experience including models, tests, macros, YAML documentation, incremental strategies, and model validation.
  • Practical AWS S3 experience with file staging, delivery paths, bucket structure, and lifecycle management.
  • Working knowledge of HIPAA de-identification and Safe Harbor requirements.
  • SDLC fundamentals, including requirements, test plans, releases, and documentation.
  • Git/GitHub and CI/CD experience with PR-based review workflows and branching strategies.
  • Experience communicating technical data topics with external customers or partner analytics/science teams.
  • Experience with Argo Workflows or a comparable orchestration platform (preferred).
  • Familiarity with patient tokenization or record linkage technologies (preferred).
  • Experience with HIPAA de-identification certification workflows (preferred).
  • Healthcare data standards such as ICD-10, CPT, NDC, LOINC, and NPI (preferred).
  • Experience at a healthcare data vendor, RWD aggregator, or analytics platform company (preferred).
  • Comfort operating in an AI-first environment using Claude or similar tools (preferred).

Benefits

  • Flexible, fully remote work environment.
  • Exposure to senior leaders across life science and corporate engineering teams.
  • Clear path to grow into a player/manager role as the team scales.
  • Opportunity to shape a high-impact RWD delivery pipeline and become the internal expert on the dataset.
  • Work in an AI-first environment with access to cutting-edge tools.
  • Support and resources to do your best work.
  • Be part of a talented, energized, diverse, and purpose-driven team.

Interested in this position?

Apply directly on the company website

Apply Now

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