Syneos Health

Senior Biometrics Data Engineer

Syneos Health

full-time

Posted on:

Location Type: Remote

Location: Arizona • Maine • United States

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Job Level

Senior

Tech Stack

AirflowAzureCloudDockerETLKubernetesPandasPySparkPythonSQL

About the role

  • Act as a hands-on technical lead who not only defines the architecture but also codes, deploys, and maintains scalable ETL pipelines and data structures
  • Spearhead the technical implementation of the Translational Data Lake data ingestion, managing the ingestion of complex datasets (genomics, proteomics, imaging, lab data, etc.) into modern cloud architectures
  • Lead data engineering projects beyond the Data Lake, designing bespoke integration solutions for diverse scientific data sources across the Research organization
  • Design and script automated procedures to normalize unformatted data from external vendors (CROs) into a structured Common Data Model (CDM)
  • Partner with various functions in Research and IT to align infrastructure with scientific needs, ensuring solutions are robust, FAIR-compliant, and scalable
  • Develop and communicate the technical vision for biomarker data integration and reuse
  • Architect and implement scalable ETL procedures, APIs and front-end tools for data access and visualization
  • Engage stakeholders to gather requirements and incorporate feedback into design
  • Lead user acceptance testing (UAT) and ensure high-quality deliverables
  • Collaborate with IT and Translational leads to align infrastructure and governance processes
  • Champion FAIR principles and interoperability across translational and clinical programs

Requirements

  • Bachelor’s or master’s degree in computer science, Data Engineering, Bioinformatics, or related field
  • 8+ years of professional experience in data engineering or software architecture, with a focus on building production-grade data pipelines
  • Expert-level coding proficiency in Python with specific mastery of modern data engineering libraries (Pandas, PySpark, Dask, SQLAlchemy)
  • Advanced proficiency with SQL, workflow orchestration tools (Airflow, Dagster, or Prefect), and containerization (Docker/Kubernetes)
  • Deep experience with modern Data Lake and Lakehouse architectures (e.g., Azure Fabric, Databricks, Snowflake)
  • Solid understanding of data modeling, ETL processes, and schema design for complex datasets
  • Experience designing and deploying APIs for data access
  • Excellent communication skills to bridge the gap between IT infrastructure and scientific stakeholders.
Benefits
  • Health benefits to include Medical, Dental and Vision
  • Company match 401k
  • Eligibility to participate in Employee Stock Purchase Plan
  • Eligibility to earn commissions/bonus based on company and individual performance
  • Flexible paid time off (PTO) and sick time
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
ETL pipelinesdata structuresdata engineeringdata modelingschema designPythonSQLAPIsworkflow orchestrationcontainerization
Soft Skills
communicationleadershipcollaborationstakeholder engagementuser acceptance testing