Senior Data Architect

1 week ago

Pune, Maharashtra, India beBeeData Full time ₹ 22,00,000 - ₹ 26,00,000
Job Overview

We are seeking a skilled senior data architect with expertise in SQL, big data processing and modern data platforms. The ideal candidate will have hands-on experience with unified data platforms like Databricks and Snowflake and exposure to Microsoft Azure Fabric.

Key Responsibilities:

  • Lead initiatives to develop and continuously improve the Data/AI Practice.
  • Design, build and optimize data pipelines for structured and unstructured datasets.
  • Implement ETL/ELT processes using SQL and modern big data frameworks.
  • Work with Modern Data Platforms to enable data integration, transformation and analytics.
  • Collaborate with architects and governance leads to ensure data quality, lineage and compliance.
  • Apply big data processing concepts like partitioning, distributed computing and streaming/batch data flows.
  • Support performance tuning, monitoring and automation of data workflows.
  • Develop data modelling processes.
  • Contribute to assessments and adoption of new vendor/platform solutions like Azure Fabric.
Required Skills & Experience

The successful candidate will possess the following skills and qualifications:

  • Ability to lead data engineering projects from inception to delivery.
  • Fluent understanding of data modelling and linking data entities.
  • Strong proficiency in SQL queries, optimization and stored procedures.
  • Solid understanding of big data processing, including distributed computing, Spark, Kafka and Delta Lake concepts.
  • Familiarity with cloud data ecosystems.
  • Strong problem-solving skills and ability to work collaboratively.
Benefits

The benefits of this role include:

  • Opportunity to work with cutting-edge technology.
  • Chance to contribute to strategic initiatives.
  • Collaborative team environment.
Others

In addition, the ideal candidate should have:

  • Experience with Microsoft Azure Fabric.
  • Knowledge of data governance tools and cataloguing concepts.
  • Exposure to DevOps/MLOps practices.

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