Manager, Data Engineering

Data Manager of Data Engineering PHM is the leading health media agency in the US, built for the modern healthcare experience. Here, industry depth meets media scale, where data becomes direction, where creativity and storytelling bring truth to life, and where orchestration replaces fragmentation. Dedicated to making brands discovered, PHM redefines what media can do through data, content, and creativity. Because in modern healthcare, the brands that are found are the ones that lead. And when brands lead, advantage follows. The Data Manager of Data Engineering will work in a hands-on and supportive role in our Technology and Data Department. This team processes and maintains all the data that flows into our organization and is the face of the agency regarding data needs from HCP publishers. You will work with internal and external partners, along with industry vendors, to monitor data transfers, perform data QA'ing and maintain documentation. You will also support the Vice President of Data Engineering to enforce enterprise-wide data processes and protocols. Responsibilities: Lead a portfolio of data projects across multiple clients Design and manage scalable pipelines, including ingestion from APIs (REST, GraphQL, vendor feeds) and traditional ETL sources Contribute to data architecture decisions to ensure efficient schema design, scalability, and governance across data warehouses and lakehouses Partner with BI, Product, and Media Tech teams to automate data integrations and improve data flow reliability Oversee ETL and metadata management to ensure stability, security, and compliance Present issues, trends, and recommendations to internal and external stakeholders Maintain best practices for handling, storing, and governing data Qualifications: BS in Computer Science, Information Technology, or related field Strong hands-on experience with PySpark (preferred language for data engineering and automation) Proficiency in Python and SQL for data processing and automation Experience building and maintaining API-based data pipelines, including authentication and error handling Solid knowledge of modern data architecture (data modeling, governance, warehouse, lakehouse) Experience with database structures, ETL, and cloud data platforms Technical documentation skills and ability to communicate complex topics in simple, user-friendly terms Specific Skills Required: Cloud platforms: AWS, Azure, Databricks Data warehouses/lakehouses: Snowflake, Redshift, Databricks Lakehouse BI tools: Tableau, Datorama (preferred) Strong collaboration skills with cross-functional teams Compensation Range: USD $88,540.00 - USD $127,155.00/Annually. Digitas