The Role
Build and maintain cloud data pipelines, transformations, orchestration workflows, governance controls, and analytics-ready datasets. Integrate APIs, Databricks, BI tools, and platform connectors while troubleshooting data quality and performance issues. Collaborate with product, engineering, DevOps, security, and client-facing teams on architecture, access management, infrastructure migrations, documentation, and production support.
Summary Generated by Built In
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 BlockBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSkills Required
- 3+ years of experience as a Data Engineer building production-grade data pipelines
- Hands-on experience with Apache Spark, PySpark, and SQL for large-scale data transformation
- Experience with cloud platforms, preferably Azure, and cloud-native data storage such as Data Lake or Blob Storage
- Experience with Databricks and familiarity with Unity Catalog or similar data governance tools
- Familiarity with data governance and RBAC or ABAC access control models for sensitive, multi-tenant data
- Experience integrating data pipelines with Power BI, Tableau, or similar visualization tools
- Understanding of software engineering practices including version control, CI/CD, testing, and code review
- Good communication skills and ability to collaborate cross-functionally with product, engineering, and client-facing stakeholders
- Experience with API-based data ingestion tools or connectors such as Adverity
- Experience with workflow orchestration tools such as Apache Airflow
- Experience with identity and access management integrations such as Okta or Entra ID
- Experience with Istio and containerized deployments using AKS or Kubernetes
- Exposure to sustainability, ESG, or carbon accounting data models
- Experience with C4 model architecture documentation using PlantUML or similar tools
dentsu Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dentsu and has not been reviewed or approved by dentsu.
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Parental & Family Support — Paid parental leave at full pay and caregiver supports (including backup care) are emphasized as standout elements. Feedback suggests family-oriented benefits are a strong part of the package.
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Leave & Time Off Breadth — Flexible or unlimited PTO, extensive paid holidays, and a year-end office closure are established components. Feedback suggests time-off policies are generous and add meaningful flexibility.
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Retirement Support — A large, established 401(k) plan with employer matching is clearly documented. Feedback suggests retirement benefits feel competitive and straightforward.
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The Company
What We Do
We are dentsu. We team together to help brands predict and plan for disruptive future opportunities and create new paths to growth in the sustainable economy. We know people better than anyone else and we use those insights to connect brand, content, commerce and experience, underpinned by modern creativity. We are the network designed for what’s next
