Data Engineer

dentsu; New Delhi; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Merkle, a data-driven solutions leader, is hiring a Data Engineer to build and maintain data platforms supporting media and sustainability analytics in Bengaluru.

You’ll ingest data from APIs and internal sources, transform with Spark and SQL, orchestrate pipelines, and ensure secure multi-tenant access. Collaboration with product managers and senior engineers is key.

This permanent, full-time role demands hands-on coding and a passion for scalable data architecture.

Qualifications

• 3+ years as a Data Engineer building production pipelines.
• Hands-on with Spark (PySpark) and SQL at scale.
• Experience on Azure cloud and cloud-native storage.
• Familiarity with Unity Catalog or similar governance tools.

Responsibilities

• Build and maintain data pipelines from APIs and internal sources into data lake/lakehouse.
• Develop transformation logic to standardize and enrich data for analytics.
• Design and manage orchestration workflows to schedule and monitor pipelines.
• Support data governance and access control for multi-tenant environments.
• Collaborate with product managers and engineers to implement platform features.

Skills

Spark / PySpark

SQL

Azure Cloud

Databricks

RBAC / ABAC

Power BI / Tableau

CI/CD / DevOps

API data ingestion

Tools

Databricks

Azure

Unity Catalog

Okta / IAM

AKS / Kubernetes

Job description

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