Senior Data Solutions Architect

4 weeks ago

Bengaluru, Karnataka, India Grid Dynamics Full time
Job Description

We are seeking a seasoned Data Architect to lead our data engineering practice at Grid Dynamics. The ideal candidate will have extensive experience in Big Data engineering, data governance, and cloud data platforms.

This role involves creating and bringing to market solutions in data engineering, MLOps, and data governance. You will be responsible for driving innovation through research and development activities on industry trends, defining Go-To-Market strategies, and developing assets and solutions strategy across multiple industries.

You will work with Grid Dynamics' delivery organization to ensure that the right tools, technologies, and processes are in place across the firm to transform and continuously improve the quality and efficiency of our clients' data platforms and data management processes.

The successful candidate will have a strong understanding of cloud-based architectures for data collection, data aggregation, reporting, and BI, as well as ML platforms and tooling including open-source, cloud native, and proprietary.

We estimate the salary for this position to be around $180,000-$220,000 per year, based on industry standards and location (Bangalore/Hyderabad).

Requirements
  • Extensive practical experience in Big Data engineering, data governance, and cloud data platforms.
  • Strong understanding of cloud-based architectures for data collection, data aggregation, reporting, and BI.
  • Strong understanding of ML platforms and tooling including open-source, cloud native, and proprietary.
  • Deep domain knowledge in at least one of the following industries: Retail, Finance, Manufacturing, Healthcare, Life Sciences.
  • Experience in managing and delivering sophisticated analytical and data engineering programs at the enterprise scale.
  • Managed key client relations worldwide and advised global technology and business leaders on innovation and data strategy.
Technology Skills
  • Data engineering: analytical data platforms, streaming, big data, EDW, data lakes, data governance, data mesh, Spark, Kafka, Snowflake.
  • Transactional databases: Redis, Cassandra, MongoDB.
  • ML and MLOps: VertexAI, Sagemaker, Dataiku, Databricks, mlflow.

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