Director - Data Engineering

**Job Description:** **Director, Data Engineering** Data Experience (DEx)  •  Decisioning  •  Dentsu Global Services (DGS) **Team:** Data Experience (DEx) — Data Engineering **Reports to:** Practice Lead / Group Lead, Data Engineering **Level:** Director (DGS) **Location:** Offshore (DGS, India) **Employment:** Dentsu Global Services About the Role ============== 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. What You'll Do ============== * Lead the offshore (DGS) Data Engineering team — setting architecture and delivery standards, reviewing code and design, mentoring engineers, and owning quality across the portfolio. * Own the Databricks Lakehouse end to end: ingestion, Medallion (bronze/silver/gold) modeling, Unity Catalog governance, Lakeflow pipelines, and performance. * Design and build robust, scalable pipelines that bring together media and marketing data from many platforms into governed, analytics-ready datasets. * Drive adoption of AI-assisted data development across the team — using Databricks Genie, Copilot, and Claude Code to accelerate pipeline build, transformation, and debugging without sacrificing rigor. * Establish and enforce data taxonomies, schema standards, data quality checks, and a single source of truth for core media data. * Partner with visualization, data science, and ad ops teams to source data correctly, validate it, and resolve discrepancies between platform truth and downstream reporting. * Contribute to the productization of the data platform — moving from bespoke, client-by-client pipelines toward reusable, standardized, semi-automated data products. * Manage capacity, utilization, and delivery health for the DGS engineering team, coordinating closely with onshore leadership on staffing and priorities. 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 ============== * 10+ 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. _Dentsu is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees._ **Location:** DGS India - Chennai - Anna Nagar Tyche Towers **Brand:** Paragon **Time Type:** Full time **Contract Type:** Permanent