9 days ago
Pune, India +4 moreStaff+
Responsibilities
- Design, build, and maintain complex ETL/ELT pipelines and transformation logic for enterprise data integrations.
- Implement incremental loads, change data capture, deduplication, slowly changing dimensions, and schema evolution.
- Develop and review Gremlin graph models and queries for Azure Cosmos DB knowledge-graph use cases.
- Develop and review SPARQL queries and Turtle ontology/data files for RDF-based semantic graph solutions.
- Set enterprise lakehouse, medallion, data mesh, data-store selection, and pipeline architecture standards.
- Own the hands-on build-out and strategy of the Azure data platform, including lake storage, Data Factory/Dataflow Gen2, Spark engineering, and real-time data flows.
- Own enterprise data catalog, lineage, classification, glossary, governance, and stewardship strategy.
- Lead, mentor, pair with, and conduct code reviews for data engineers while debugging production pipelines.
- Partner with architects, AI engineering leads, and stakeholders to create and deliver the data strategy roadmap.
- Own data security, access control, compliance, RBAC, sensitivity labeling, and audit posture across the platform.
Requirements
- At least 12 years of data engineering or data platform experience, including at least 5 years leading data engineering teams or platform initiatives.
- Strong hands-on experience building enterprise ETL/ELT pipelines on Azure or an equivalent modern data platform.
- Strong Python, Spark/PySpark, and SQL skills for transformation and analytical or transactional workloads.
- Proven experience building and operating enterprise-scale bronze, silver, and gold lakehouse pipelines.
- Hands-on experience with Gremlin and graph data models in Azure Cosmos DB for Apache Gremlin.
- Hands-on experience with RDF/semantic graph technologies, SPARQL, Turtle files, and triplestores such as Graphwise GraphDB, Amazon Neptune, or Stardog.
- Experience designing and implementing data mesh operating models, self-service platforms, domain ownership, data products, and federated governance.
- Experience owning enterprise data catalog and governance tooling such as Microsoft Purview.
- Experience integrating and rationalizing data from heterogeneous enterprise source systems.
- Experience mentoring engineers through pairing and code review and presenting architecture or strategy to senior stakeholders.
- Preferred experience with RDF/RDFS, OWL, SHACL, SKOS, ontology-driven knowledge graphs, and semantic layers.
- Preferred experience with Apache Airflow or Fabric-based orchestration, AWS, Azure, GCP, vector stores, RAG or agentic AI data preparation, Eventstream, KQL, and regulated-industry governance.
Benefits
- The role is located in India.
Tech Stack
Categories
Data Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.