Job Description:About the RoleWe 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 DoBuild and maintain data pipelines that ingest data from third-party APIs and internal sources into cloud data lake and lakehouse environmentsDevelop data transformation logic (Spark/PySpark, SQL) to standardize, model, and enrich raw data into analytics-ready datasetsBuild and maintain orchestration workflows to schedule, monitor, and troubleshoot data pipeline executionSupport 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 marketWork with product managers and senior engineers to implement platform features such as connector frameworks, taxonomy/rules engines, and data export capabilitiesSupport integration with visualization and reporting tools (e.g. Power BI, Tableau) and help ensure downstream data consumers have reliable, well-documented accessContribute to architecture documentation (e.g. C4 model diagrams) and participate in design reviewsTroubleshoot data quality, pipeline failures, and performance issues, tracing errors from source to destinationWork 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 pipelinesWhat You'll Bring3+ years of experience as a Data Engineer building production-grade data pipelinesSolid hands-on experience with Apache Spark (PySpark) and SQL for data transformation at scaleExperience 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 toolsFamiliarity with data governance and access control models (RBAC/ABAC), and working with sensitive, multi-tenant dataExperience 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 plusSolid understanding of software engineering practices: version control, CI/CD, testing, code reviewGood communication skills and ability to work cross-functionally with product, engineering, and client-facing stakeholdersNice to HaveExperience with workflow orchestration tools such as Apache AirflowExperience 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 modelsExperience with C4 model architecture documentation (PlantUML or similarLocation:DGS India - Bengaluru - Manyata N1 BlockBrand:MerkleTime Type:Full timeContract Type:Permanent