Data Architecture & Data Engineering Leader

Role overview

Lead the design and operation of an enterprise data platform that supports analytics, client reporting, and commercial data products. This hands-on leadership role sets the data architecture and roadmap, builds scalable data services and pipelines, and develops a distributed engineering team while ensuring the platform is reliable, governed, and secure.

Responsibilities - Define the data architecture roadmap, document data flows and source mappings, establish engineering standards, and assess technology choices, cost, and performance. - Own cloud data platform development, lead consolidation of reporting systems, and deliver batch and streaming pipelines from client, vendor, media, and first-party sources. - Build reusable, governed datasets and data services for client-facing products, with multi-client access controls, data contracts, versioning, and service expectations. - Partner with product and business leaders to assess data requirements, feasibility, quality, licensing, compliance, and ongoing delivery costs for new offerings. - Automate ingestion, transformation, validation, refreshes, and client feeds; establish data quality checks, monitoring, alerting, and service levels. - Set data governance and security practices, including access, classification, lineage, retention, auditing, and vendor data handling. - Hire, lead, and mentor data engineers and analysts, introduce sound delivery practices, and communicate technical recommendations to business leaders.

Requirements - At least 16 years in data engineering or architecture, including five or more years leading technical teams. - Track record designing and operating enterprise cloud data platforms; Google Cloud and BigQuery experience are preferred. - Experience building data foundations for commercial products or client-facing platforms, as well as consolidating platforms or migrating legacy sources. - Strong hands-on SQL and Python skills, data modeling experience, and familiarity with orchestration and transformation tools such as Airflow, Cloud Composer, or dbt. - Background in data quality, observability, governance, security, privacy, and compliance for sensitive or regulated data. - Ability to build standards and documentation in an organization with developing technical practices, and to lead teams across time zones.

Nice to have

- Experience in media, advertising, marketing technology, healthcare, or pharmaceutical marketing, including HCP data, NPI matching, campaign data, or marketing analytics. - Familiarity with data products, multi-tenant delivery, data licensing, AI-assisted engineering, BI, integration, catalog, or lineage tools. - Google Cloud data or architecture certification and experience leading distributed teams in Europe.

Benefits and work setup

- Remote role for candidates located in the United States; preference is given to candidates in the Eastern time zone or willing to work those hours. The team includes members in Poland.