Director, Data Management

Publicis Groupe Holdings B.V; Chicago (IL); On-site; USD 135,000 - 194,000; Full time

Job summary

Spark Foundry, part of Publicis Groupe, seeks a Director of Data Management Lead to own end‑to‑end data governance and backend architecture across media and pharmaceutical data. You will lead cross‑functional teams, set standards, and drive data quality and security initiatives to enable reporting, measurement, and advanced analytics.

You will partner with privacy, security, and client teams, translating complex requirements into scalable data solutions while guiding offshore delivery and

Qualifications

• 8–10+ years of experience in data management, data engineering, analytics engineering, media data operations, or data governance within an agency, pharmaceutical, or similarly complex environment.
• Demonstrated leadership of client‑facing data programs, with the ability to own the overall approach, facilitate technical and functional decisions, and communicate risks and recommendations.
• Strong hands‑on experience with Databricks and/or Snowflake, SQL, Python, data modeling, ETL/ELT, orchestration, testing, monitoring, and production support.
• Deep understanding of media and marketing data across digital and offline channels, including campaign hierarchies, taxonomies, platform extracts, delivery metrics, and reporting dependencies.
• Proven experience establishing data governance, quality controls, reconciliation processes, error tracking, lineage, metadata, and operational SLAs.
• Ability to translate business requirements into scalable technical designs and to review or build data flows when delivery requires hands‑on support.
• Strong understanding of privacy, security, data handling, auditability, and compliance principles in regulated environments.
• Excellent leadership, stakeholder management, documentation, problem‑solving, and communication skills across technical and non‑technical audiences.

Responsibilities

• Own data governance operating model across media, measurement, and pharmaceutical data domains.
• Lead ingestion, validation, reconciliation, monitoring, and delivery of media data across sources.
• Guide client, media, analytics, engineering, privacy, security, and offshore teams through clear requirements and RACIs.
• Provide technical direction for scalable backend architecture in Databricks and Snowflake.
• Translate reporting and analytics needs into data models, mappings, and acceptance criteria.
• Lead by example with hands‑on SQL, Python, notebooks, and data pipelines.
• Promote data engineering best practices for modularity, testing, and cost efficiency.

Skills

Data leadership

Data governance

SQL

Python

Stakeholder management

Tools

Databricks

Snowflake

ETL/ELT

CI/CD

Job description

Company description

Spark Foundry was built during the most transformative time in the history of advertising and marketing. We deliver everything a traditional media agency has to offer and have grown into one of the world’s most successful agencies by helping brands evolve their marketing by leveraging identity, commerce, artificial intelligence, and more to connect with people. Transformation is part of our DNA. Spark Foundry’s start-up spirit delivers high-touch approaches and a never-ending desire to challenge the status quo. Combined with Publicis Media’s powerhouse soul leveraging connected data assets, advanced AI applications, and investment clout, we “Bring HEAT to Brands.” No other agency possesses the expertise that we do to address today’s most pressing challenges to drive business transformation through media.

Overview

The Director, Data Management Lead is the primary client and agency point of contact for media and pharmaceutical data management. This role defines the end-to-end data management approach, guides backend architecture in Databricks and Snowflake, and ensures that data is accurate, secure, compliant, traceable, and fit for reporting, measurement, optimization, and advanced analytics.

Embedded within the Data & Analytics organization, this role blends functional data leadership with hands‑on engineering. The lead partners across client, media, analytics, technology, privacy, and offshore teams; brings forward scalable data engineering best practices; and can roll up their sleeves to design, build, troubleshoot, and optimize data flows. Knowledge of pharmaceutical media, HCP data, privacy and compliance requirements, and applied AI is highly valued.

Responsibilities

1) Data Governance Strategy & Data Health

• Own the client and agency data management and governance operating model across media, measurement, and pharmaceutical data domains.
• Define standards for data ownership, lineage, metadata, naming conventions, taxonomies, access, retention, and fitness for use.
• Establish measurable data health controls, SLAs, stewardship routines, issue escalation paths, and governance forums.
• Translate regulatory, privacy, security, and client requirements into practical controls, with working knowledge of HCP and other sensitive pharmaceutical datasets considered a strong advantage.

2) Media Data Operations & Quality Management

• Lead ingestion, validation, reconciliation, monitoring, and delivery of media data across paid search, social, programmatic, video, display, offline, and publisher sources.
• Design media data quality guardrails, automated checks, thresholds, and exception handling across source-to-report pipelines.
• Own error tracking and defect management, including triage, root-cause analysis, remediation ownership, SLA monitoring, and prevention of recurrence.
• Ensure transformed and harmonized datasets reconcile to source systems and satisfy reporting, measurement, optimization, and audit requirements.

3) Cross-Functional Process Leadership

• Serve as the primary point of contact for client data discussions, including data strategy, architecture, onboarding, quality, governance, issue resolution, compliance, and delivery readiness.
• Guide client, media, analytics, engineering, ad operations, privacy, security, and offshore teams through clear requirements, RACIs, decisions, dependencies, risks, and escalation paths.
• Lead source onboarding and change management so media plans, buys, identifiers, taxonomies, and required metadata flow correctly into downstream platforms.
• Build trusted client relationships by communicating technical topics in business terms and providing clear recommendations, trade-offs, owners, and next steps.

4) Data Architecture, Business Rules & Transformation Enablement

• Provide technical direction for scalable backend architecture in Databricks and/or Snowflake, covering ingestion, medallion or layered design, transformation, orchestration, storage, performance, security, and observability.
• Translate functional reporting and analytics needs into data models, mapping specifications, business rules, validation logic, BRDs, TRDs, and engineering-ready acceptance criteria.
• Lead by example and contribute hands‑on when needed by building, reviewing, troubleshooting, and optimizing SQL, Python, notebooks, jobs, and data pipelines.
• Bring forward data engineering best practices for modularity, reuse, testing, deployment, documentation, cost efficiency, recoverability, and production support.

5) Training, Compliance & Change Management

• Partner with client privacy, legal, security, and compliance stakeholders to interpret requirements and embed appropriate access, handling, masking, retention, transfer, and audit controls.
• Promote compliant use of HCP, patient‑adjacent, audience, identity, and media data without compromising analytical utility or operational clarity.
• Develop playbooks, standards, job aids, templates, and training for onshore and offshore teams, explaining both the control and the business rationale behind it.
• Monitor adoption, document evidence, and improve processes when controls or operating practices break down.

6) Global Stewardship & Continuous Improvement

• Serve as the accountable day‑to‑day lead for data operations, platform health, governance, and engineering delivery across markets and workstreams.
• Maintain a prioritized improvement roadmap spanning automation, reusable frameworks, monitoring, documentation, performance, cost, and operational resilience.
• Evaluate and responsibly apply AI‑assisted capabilities for data quality, anomaly detection, metadata management, engineering productivity, and operational support.
• Provide leadership and clients with concise updates on data health, delivery, risks, blockers, decisions, ownership, and measurable business impact.

Qualifications

• 8–10+ years of experience in data management, data engineering, analytics engineering, media data operations, or data governance within an agency, pharmaceutical, or similarly complex environment.
• Demonstrated leadership of client‑facing data programs, with the ability to own the overall approach, facilitate technical and functional decisions, and communicate risks and recommendations.
• Strong hands‑hand experience with Databricks and/or Snowflake, SQL, Python, data modeling, ETL/ELT, orchestration, testing, monitoring, and production support.
• Deep understanding of media and marketing data across digital and offline channels, including campaign hierarchies, taxonomies, platform extracts, delivery metrics, and reporting dependencies.
• Proven experience establishing data governance, quality controls, reconciliation processes, error tracking, lineage, metadata, and operational SLAs.
• Ability to translate business requirements into scalable technical designs and to review or build data flows when delivery requires hands‑hand support.
• Strong understanding of privacy, security, data handling, auditability, and compliance principles in regulated environments.
• Excellent leadership, stakeholder management, documentation, problem‑solving, and communication skills across technical and non‑technical audiences.

Preferred Experience

• Experience with pharmaceutical media and regulated data, including familiarity with HCP data, identity, consent, privacy, and compliant activation or measurement workflows.
• Experience designing lakehouse or warehouse architectures and CI/CD practices in cloud data environments.
• Familiarity with media buying, ad serving, audience, measurement, and publisher platforms and their data delivery patterns.
• Experience with data observability, catalog, lineage, master/reference data, and quality monitoring frameworks.
• Working knowledge of AI/ML concepts and practical AI‑assisted use cases in data engineering and governance.
• Strong program management discipline, including roadmaps, RACIs, dependency tracking, release planning, and executive status reporting.

Tools & Platforms

• Core engineering: Databricks, Snowflake, SQL, Python, notebooks, ETL/ELT, orchestration, APIs, file transfers, and version control/CI‑CD practices
• Governance and operations: data catalogs, lineage, quality and observability tools, issue/error tracking, access controls, documentation, and collaboration platforms
• Business intelligence and analytics: Power BI and comparable reporting, transformation, and workflow tools
• Media and measurement platforms: Campaign Manager 360, DV360, The Trade Desk, paid social platforms, Amazon DSP, Google Analytics, Adobe Analytics, Prisma, and related agency/client systems

Additional information

Our Publicis Groupe motto “Viva La Différence” means we’re better together, and we believe that our differences make us stronger. It means we honor and celebrate all identities, across all facets of intersectionality, and it underpins all that we do as an organization. We are focused on fostering belonging and creating equitable & inclusive experiences for all talent.

Publicis Groupe provides robust and inclusive benefit programs and policies to support the evolving and diverse needs of our talent and enable every person to grow and thrive. Our benefits package includes medical coverage, dental, vision, disability, 401K, as well as parental and family care leave, family forming assistance, tuition reimbursement, and flexible time off.

If you require accommodation or assistance with the application or onboarding process specifically, please contact [e-mail].

All your information will be kept confidential according to EEO guidelines.

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Compensation Range: USD $135,375.00 - USD $194,460.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third‑party benefits administration system once certain criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 10/11/2026.