6 days ago
Remote, India or Bengaluru, IndiaStaff+
Responsibilities
- Design, build, test, deploy, and support production data pipelines, analytics, ML, and GenAI solutions on Google Cloud.
- Develop data platforms and modernize warehouses and lakehouses using BigQuery, BigLake, Dataflow, Dataproc, Datastream, and Cloud Composer.
- Deliver governed self-service analytics, customer intelligence, real-time streaming, generative AI, agentic AI, and applied ML solutions.
- Translate client business and data challenges into target-state data and AI architectures and serve as a trusted technical advisor.
- Lead and mentor onshore/offshore teams, conduct design and code reviews, and collaborate with data, product, security, and business stakeholders.
- Apply DataOps, MLOps, Terraform, automated testing, and CI/CD using an Agile delivery model.
- Own data quality, service-level agreements, lineage, access control, security, reliability, performance, and cloud cost optimization.
- Contribute to points of view, reusable accelerators, reference architectures, estimates, proposals, and offering development.
Requirements
- Hands-on experience delivering GCP data and AI products through design, build, and production operation, rather than only hosting custom development on GCP.
- Strong Python and SQL skills; Java or Scala with Apache Beam is a plus.
- Deep Google Cloud data engineering experience with BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer or Dataform, Cloud Storage or BigLake, and Datastream.
- Experience with Vertex AI, BigQuery ML, Gemini, retrieval-augmented generation, Vector Search, and agent frameworks such as Agent Builder or ADK.
- Knowledge of Terraform, infrastructure as code, CI/CD, DataOps, MLOps, observability, IAM, VPC Service Controls, CMEK, DLP, and Dataplex.
- Domain depth in one or more Google Cloud Data and AI areas, including data platforms, analytics, GenAI, applied ML, customer intelligence, streaming, or governance and security.
- Strong solutioning and offering skills, including reusable assets, points of view, estimation, and value-based outcomes.
- Google Cloud Professional Data Engineer, ML Engineer, or Cloud Architect certification is preferred.
- Experience with Looker, LookML, Dataplex governance, and Analytics Hub data sharing is preferred.
- Experience leading onshore/offshore Agile teams is preferred.
Tech Stack
Categories
Data EngineeringML 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.