The Data Experience (DEx) practice builds the data foundations, pipelines, and products that power Dentsu's media and marketing effectiveness work across Carat, iProspect, and Dentsu X. We are seeking a Director, Data Engineering to lead our offshore (DGS) engineering capability — owning the architecture, quality, and delivery of the data platform that everything downstream depends on.
This is a senior leadership and hands-on engineering role. You will set the standard for how DEx ingests, models, and serves media and marketing data on Databricks, and you will do it as a modern practitioner — using AI-assisted data development (Databricks Genie, Copilot, Claude Code) to move faster and raise quality. You will lead and mentor a team of DGS engineers while staying close enough to the code to set the bar yourself. This role demands deep Databricks expertise and a genuine understanding of what media data means, not just how to move it.
Job Description:
Core Skills & Requirements
Databricks & Data Engineering
- Deep, hands-on Databricks expertise: Spark, Delta Lake, Unity Catalog, Lakeflow / Delta Live Tables, Medallion architecture, and performance tuning.
- Expert-level SQL and strong Python for data engineering; production experience building and operating pipelines at scale.
- Solid grasp of data modeling, orchestration, data quality, and governance — building for reuse and maintainability, not one-off delivery.
- Experience with the surrounding ecosystem (Azure, lightweight ETL / data-prep tooling such as Trifacta or dbt) is a strong plus.
AI-Assisted Data Development
- Hands-on experience developing data solutions with AI tooling — Databricks Genie, GitHub / Databricks Copilot, Claude Code, or comparable AI coding agents.
- Able to use AI assistants to accelerate pipeline build, transformation logic, and debugging while maintaining correctness, governance, and quality.
- A builder's mindset: comfortable pairing with AI tools as a force multiplier for the team, not a novelty.
Media & Marketing Data Fluency
You must understand not just how to engineer the data, but what the data means.
- Strong command of media and marketing data: what impressions, spend, clicks, and conversions represent, and how they relate.
- Understanding of how reach and frequency work — served vs. viewable impressions, de-duplicated reach, and frequency capping — and the implications for how data must be modeled.
- Familiarity with conversion tracking and attribution mechanics — pixels, tags, post-click vs. post-view, and lookback windows.
- Knowledge of how media data connects across campaigns, placements, creatives, and channels, and how spend flows through to outcomes.
- Practical experience with media taxonomies and naming conventions as the foundation of trustworthy, joinable data.
Leadership
- Proven experience leading and developing an engineering team, ideally in an offshore / DGS or global delivery model.
- Ability to set architecture and code standards, review work critically, and raise the quality bar across a team.
- Strong communication across time zones with onshore leads and stakeholders.
Preferred / Nice to Have
- Experience with streaming / near-real-time ingestion patterns.
- Familiarity with trafficking / ad ops platforms (CM360, Prisma, DV360, TTD) and how their data lands in the platform.
- Exposure to semantic / metrics layers and how engineering choices affect downstream reporting (Power BI, dbt metrics).
- Experience in an agency, ad tech, or marketing analytics environment.
- CI/CD, testing, and DataOps practices for data pipelines.
Qualifications
- 12+ years in data engineering, with several years in a leadership or director-level capacity.
- Demonstrated deep Databricks / Lakehouse expertise in production.
- Demonstrated domain knowledge of media and/or marketing data (hard requirement).
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Location:
DGS India - Chennai - Anna Nagar Tyche Towers
Brand:
Paragon
Time Type:
Full time
Contract Type:
Permanent
