Dentsu

Marketing analytics and digital advertising solutions

Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeNo salary listedIn-person

About the Job

Requirements

At least 3 years of experience as a Data Engineer building production-grade data pipelines.
Hands-on experience with Apache Spark, PySpark, and SQL for data transformation at scale.
Experience with cloud platforms, preferably Azure, and cloud-native data storage such as Data Lake or Blob Storage.
Experience with Databricks, including Unity Catalog or similar data governance and catalog tools.
Familiarity with data governance and access control models such as role-based access control and attribute-based access control, including work with sensitive, multi-tenant data.
Experience integrating data pipelines with business intelligence and visualization tools such as Power BI or Tableau.
Solid understanding of software engineering practices, including version control, continuous integration and continuous delivery, testing, and code review.
Ability to work cross-functionally with product, engineering, and client-facing stakeholders.

Responsibilities

Build and maintain data pipelines that ingest data from third-party application programming interfaces and internal sources into cloud data lake and lakehouse environments.
Develop data transformation logic using Spark, PySpark, and SQL to standardize, model, and enrich raw data into analytics-ready datasets.
Build and maintain orchestration workflows to schedule, monitor, and troubleshoot data pipeline execution.
Support data governance and access control models, including Unity Catalog and attribute-based access control policies, to ensure data is secure and appropriately scoped by tenant, client, or market.
Work with product managers and senior engineers to implement platform features such as connector frameworks, taxonomy and rules engines, and data export capabilities.
Support integration with visualization and reporting tools such as Power BI and Tableau, and help ensure downstream data consumers have reliable, well-documented access.
Contribute to architecture documentation, including C4 model diagrams, and participate in design reviews.
Troubleshoot data quality, pipeline failures, and performance issues by tracing errors from source to destination.
Work with DevOps and security teams on service account management, credential handling, and infrastructure migrations such as containerization.
Participate in on-call and support rotations for production data pipelines as needed.

Desired Qualifications

Experience with API-based data ingestion tools or connectors such as Adverity or similar platforms.
Experience with workflow orchestration tools such as Apache Airflow.
Experience with identity and access management integrations such as Okta and Entra ID.
Experience with service mesh technologies such as Istio and containerized deployments using AKS or Kubernetes.
Exposure to sustainability, environmental, social, and governance, or carbon accounting data models.
Experience with C4 model architecture documentation using PlantUML or similar tools.

Job Description:

About the Role

We are looking for a Data Engineer to join our data engineering team, building and maintaining the platforms that ingest, transform, and serve data for our media and sustainability analytics products. You will work on self-serve data platforms used by internal teams and clients to connect data sources, apply business logic and taxonomies, and deliver clean, trusted data into reporting and analytics tools. This is a hands-on engineering role where you'll take ownership of well-scoped components while working closely with senior engineers on broader architectural decisions.

What You'll Do

Build and maintain data pipelines that ingest data from third-party APIs and internal sources into cloud data lake and lakehouse environments
Develop data transformation logic (Spark/PySpark, SQL) to standardize, model, and enrich raw data into analytics-ready datasets
Build and maintain orchestration workflows to schedule, monitor, and troubleshoot data pipeline execution
Support data governance and access control models (e.g. Unity Catalog, ABAC-based policies) to help ensure data is secure and appropriately scoped by tenant, client, or market
Work with product managers and senior engineers to implement platform features such as connector frameworks, taxonomy/rules engines, and data export capabilities
Support integration with visualization and reporting tools (e.g. Power BI, Tableau) and help ensure downstream data consumers have reliable, well-documented access
Contribute to architecture documentation (e.g. C4 model diagrams) and participate in design reviews
Troubleshoot data quality, pipeline failures, and performance issues, tracing errors from source to destination
Work with DevOps/security teams on service account management, credential handling, and infrastructure migrations (e.g. containerization)
Participate in on-call/support rotations as needed for production data pipelines

What You'll Bring

3+ years of experience as a Data Engineer building production-grade data pipelines
Solid hands-on experience with Apache Spark (PySpark) and SQL for data transformation at scale
Experience with cloud platforms (Azure preferred) and cloud-native data storage (e.g. Data Lake / Blob Storage)
Experience with Databricks, including familiarity with Unity Catalog or similar data governance/catalog tools
Familiarity with data governance and access control models (RBAC/ABAC), and working with sensitive, multi-tenant data
Experience integrating data pipelines with BI/visualization tools (Power BI, Tableau, or similar)
Comfortable working with API-based data ingestion tools/connectors (e.g. Adverity or similar ingestion platforms) is a plus
Solid understanding of software engineering practices: version control, CI/CD, testing, code review
Good communication skills and ability to work cross-functionally with product, engineering, and client-facing stakeholders

Nice to Have

Experience with workflow orchestration tools such as Apache Airflow
Experience with identity/access management integrations (Okta, Entra ID)
Experience with service mesh technologies (Istio) and containerized deployments (AKS/Kubernetes)
Exposure to sustainability, ESG, or carbon accounting data models
Experience with C4 model architecture documentation (PlantUML or similar

Location:

DGS India - Bengaluru - Manyata N1 Block

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent

About the Company

Dentsu

Marketing analytics and digital advertising solutions

Dentsu International is a global marketing and advertising partner that helps brands grow by navigating the digital economy and using data-driven insights. Its services include consumer intelligence to understand customer behavior, digital marketing and advertising to reach audiences, customer experience management (CXM) to improve interactions, and gaming solutions to engage audiences. The company earns revenue through service fees, project work, and long-term contracts with a diverse mix of clients across retail, technology, and entertainment. Its approach combines research and analysis to set industry-focused insights and drive growth, while collaborating across disciplines to deliver integrated marketing solutions. Dentsu also pursues social impact initiatives, promoting inclusion and positive change in the industry and communities.

Company size: 10,001+
Company stage: IPO
Headquarters: Tokyo, Japan
Founded: 1901

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