Principal Data Architect

4 weeks ago


Charleston, West Virginia, United States Syneos Health - USA Full time
Principal Data Architect

The Technology & Data Solutions (TDS) business unit is the Syneos Health accelerator for life sciences innovation.

TDS houses our advanced technology acquisitions, homegrown products & applications, actively participates in new M&A and partnership activities, delivers critical insights as part of our integrated strategy for customers and drives enterprise-wide adoption and change management for innovative tech & data solutions.

Our work supports getting meaningful new medicines to patients faster, with greater positive impact.

The Principal Data Architect supports our business goals by designing data infrastructure to extract and organize data to support the needs of our customers.

Job Responsibilities

  • Lead and manage the design, testing, and implementation of databases (Azure SQL and/or Snowflake) that support productionized BI dashboards (PowerBI, Tableau) and custom analytic applications.
  • Provide recommendations for maintenance and optimization options related to data storage and delivery that includes plans for integrating internal enterprise data resources (e.g., Veeva, Salesforce MC) and external third-party data sources.
  • Set up database QC monitoring resources, and help troubleshoot issues related to data ingestion, security, and technical resources and pipeline failures.
  • Document and organize findings including data retrieval, stand up libraries.
  • Replicate results and present to management and/or customers as required.
  • Work alongside data engineers to develop comprehensive automated ELT workflows that align with database design.
  • Drive and influence the process for how data are organized, transferred, and assembled in support of analytic, operational, and business intelligence reporting for our product development team.
  • Communicate and translate business requirements into actionable technical work plans that are executed by data engineers and product developers.
  • Design and develop data models that support our enterprise client-facing healthcare analytic product line e.g., dashboards, apps, widgets, automated reporting).
  • Design and help build database and data service infrastructure components that support pipelines between multiple internal and external data sources.
  • Develop conceptual and production-level data models (with associated metadata) that include data lineage and definitions.
  • Define the context for data tiers and communicate the impact of how data input streams, design choices, and feature additions affect those tiers.
  • Guide and help develop data-mastering strategy for client engagements.
  • Help drive, document, and create template schemas for production level applications.
  • Collaborate with technical team members to manage, maintain, and document data security capabilities associated with technical product development.
  • Help implement and enforce enterprise reference architecture and ensure that data infrastructure design reflects enterprise business rules as well as data governance and security guidelines.
  • Mentor and coach junior team members across the business.
#LI-KW1

Qualifications

Qualification Requirements

  • Degree (BS/BA, MS/MA preferred) in Information Systems, Software Engineering, Computer Science, Data Engineering, or related field is required.
  • Experience with Azure stack (Data Lake/Blob Storage, PowerBI services, Azure Data Factory (or equivalent), Databricks) and production level experience with on-premises Microsoft SQL Server
  • Experience with Snowflake or other cloud data warehouse tools.
  • Concise and clear written and oral communication. Proven experience with delivering insights and reports to customers. Strong attention to detail.
  • Experience with healthcare marketing analytics, healthcare data (claims) and common medical coding sets (ICD, HCPCs, NPIs).
  • Familiarity with agile and lean concepts that drive towards MVPs and iterative learning to generate the desired business/technology outcomes.
  • Strong experience working with complex data ecosystems; data hubs required.
  • Strong hands-on experience with dimensional data modeling and data modeling tools required.

Disclaimer:
Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities.

Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description.

The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above. Further, nothing contained herein should be construed to create an employment contract. Occasionally, required skills/experiences for jobs are expressed in brief terms.

Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees.

The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.


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