Job Description:
We are seeking a Director, Staff Data Engineer to serve as the senior hands‑on engineer within the Data Architecture & Solutions pillar. In this role, you will translate the VP’s architecture strategy into working, scalable infrastructure. You will design systems, write production‑ready code, review architecture, and uphold engineering standards across onshore and offshore teams.
You will take ownership of the most complex builds, solve deep technical challenges, and set the code quality bar for the team.
Reports To: VP, Data Architecture & SolutionsKey Responsibilities- Architect and build complex components of dentsu’s enterprise data platform across Azure, Databricks, PySpark, Lakeflow, and Power BI.
- Lead the development of multi‑client Databricks environments, cross‑agency data federation solutions, and Lakeflow Declarative Pipelines using serverless compute.
- Drive adoption of engineering standards, coding practices, and architectural patterns defined by the VP, ensuring consistency across all delivery teams.
- Build and optimize Lakeflow Declarative Pipelines (formerly DLT) and Lakeflow Connect ingestion pipelines to support Programmatic and Search data at scale.
- Design and implement data governance frameworks including Unity Catalog policies, attribute‑based access control (ABAC), data lineage, and tag‑driven security.
- Lead technical hiring assessments and onboarding for new Data Engineering talent.
- Mentor and develop Senior Data Engineers and Data Engineers across onshore and offshore teams.
- Collaborate with the Director, Staff AI Engineer on shared infrastructure to support agentic workloads.
- Manage technical debt, platform migrations, and modernization efforts across client environments.
- Serve as the first escalation point for complex data engineering challenges before they reach the VP.
- 8+ years of data engineering experience, including 2+ years in a technical leadership or staff‑level role.
- Expert‑level experience with Databricks (Unity Catalog, Lakeflow Declarative Pipelines, serverless compute), PySpark, and enterprise lakehouse architecture.
- Strong experience with Azure cloud infrastructure, including ADLS, ADF, Azure DevOps, and Azure networking.
- Advanced PySpark and Lakeflow Declarative Pipelines skills with experience building and maintaining large‑scale data transformation pipelines.
- Strong data architecture knowledge across multiple modeling approaches (e.g., dimensional, data vault, medallion).
- Demonstrated ability to define engineering standards and drive adoption across teams.
- Experience with data governance, security, and compliance in multi‑tenant environments.
- Strong communication skills with the ability to explain technical decisions to leadership audiences.
- Experience scaling a single‑client data stack into an enterprise multi‑client deployment model.
- Background in media, advertising, or marketing technology environments.
- Experience with Lakeflow Connect managed ingestion connectors and enterprise data mesh patterns.
- Experience managing Power BI at scale (Premium capacity, deployment pipelines, semantic models).
- Experience mentoring or managing offshore engineering teams.
- Familiarity with Adverity, Lakeflow Connect, or similar media data integration platforms.
The annual salary range for this position is $113,000 - $160,000. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law.
Benefits available with this position include:
• Medical, vision, and dental insurance,
• Life insurance,
• Short-term and long-term disability insurance,
• 401k,
• Flexible paid time off,
• At least 15 paid holidays per year,
• Paid sick and safe leave, and
• Paid parental leave.
Dentsu also complies with applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, in accordance with its plans and policies. For further details regarding Dentsu benefits, please visit www.dentsubenefitsplus.com.
At dentsu, we believe great work happens when we’re connected. Our way of working combines flexibility with in-person collaboration to spark ideas and strengthen our teams. Employees who live within a commutable distance of one of our hub offices, currently located in Chicago, metro Detroit, Los Angeles, and New York City, are required and expected to work from the office three days per week (two days per week for employees based in Los Angeles). Dentsu may designate other Hub offices at any time. Those who live outside a commutable range may be designated as remote, depending on the role and business needs. Regardless of your work location, we expect our employees to be flexible to meet the needs of our Company and clients, which may include attendance in an office.
Location:
New YorkBrand:
Dentsu MediaTime Type:
Full timeContract Type:
PermanentDentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color, national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.
Dentsu is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with us, please send an e-mail to [email protected] by clicking on the link to let us know the nature of your accommodation request and your contact information. We are here to support you.
Skills Required
- 8+ years of data engineering experience, including 2+ years in a technical leadership or staff-level role
- Expert-level experience with Databricks (Unity Catalog, Lakeflow Declarative Pipelines, serverless compute)
- Advanced PySpark skills and experience building and maintaining large-scale data transformation pipelines
- Strong experience with Azure cloud infrastructure, including ADLS, ADF, Azure DevOps, and Azure networking
- Experience with enterprise lakehouse architecture and multiple data modeling approaches (dimensional, data vault, medallion)
- Experience designing and implementing data governance frameworks, ABAC, data lineage, and tag-driven security
- Ability to define engineering standards, coding practices, and architectural patterns and drive adoption
- Strong communication skills with the ability to explain technical decisions to leadership audiences
- Lead technical hiring assessments, onboarding, mentoring, and development of senior and mid-level data engineers
- Experience scaling a single-client data stack into an enterprise multi-client deployment model
- Background in media, advertising, or marketing technology environments
- Experience with Lakeflow Connect managed ingestion connectors and enterprise data mesh patterns
- Experience managing Power BI at scale (Premium capacity, deployment pipelines, semantic models)
- Experience mentoring or managing offshore engineering teams
- Familiarity with Adverity or similar media data integration platforms
