Director - Business Intelligence
DGS India - Chennai - Anna Nagar Tyche Towers
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time · Permanent — employment source
Time Type: Full time Contract Type:
Contract Type: Permanent
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingOwn architecture, quality and delivery of the media data platform
Set standards for ingesting, modeling and serving media data on Databricks
Lead and mentor a team of DGS engineers
Use AI-assisted tools to speed up pipeline build and debugging
From the employer’s posting
owning the architecture, quality, and delivery of the data platform
You will set the standard for how DEx ingests, models, and serves media and marketing data on Databricks
You will lead and mentor a team of DGS engineers
using AI-assisted data development (Databricks Genie, Copilot, Claude Code) to move faster and raise quality
What you’ll bring
All qualificationsCore experience
- 12+ years in data engineering, with several years in a leadership or director-level capacity.
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Qualification wording
12+ years in data engineering, with several years in a leadership or director-level capacity.
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Tools in this posting
- Python
- SQL
- Azure
- Databricks
- dbt
- Delta Lake
- Power BI
Source — Tool mentions in context
- 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.
- 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
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.
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.
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.
- 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).
- 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.
Posting record
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- Live
- First seen by us
- Aug 13, 2026 · 78 days ago
- Recorded sightings
- 154
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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.
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 & RequirementsDatabricks & 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.
- 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.
- 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 TowersBrand:
ParagonTime Type:
Full timeContract Type:
PermanentSource details
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