Chief Data Architect

24 hours ago

Bhavnagar, Gujarat, India beBeeData Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

About the Role

We are seeking a highly skilled Data Engineer with strong expertise in SQL, big data processing, and modern data platforms.

This role will support the design, development, and optimisation of scalable data projects.

The ideal candidate will have hands-on experience with modern unified data platforms (e.g. Databricks, Snowflake) and exposure to cloud-based technologies.

Key Responsibilities:

  • Design, build, and optimise data pipelines for large-scale 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 (e.g., partitioning, distributed compute, streaming/batch data flows).
  • Support performance tuning, monitoring, and automation of data workflows.
  • Build data modelling processes.
  • Contribute to assessments and adoption of new vendor/platform solutions.

Requirements:

  • Ability to lead data engineering projects from inception to delivery, harnessing effective communication skills to a non-technical audience.
  • Fluent understanding of data modelling to link data entities.
  • Strong proficiency in SQL (queries, optimization, stored procedures).
  • Solid understanding of big data processing (distributed computing, Spark, Kafka, Delta Lake concepts, data partitioning, schema evolution).
  • Familiarity with cloud data ecosystems.
  • Strong problem-solving skills and ability to work in a collaborative team environment.

Benefits:

  • Opportunity to work on high-profile data projects.
  • Collaborative and dynamic work environment.
  • Professional development opportunities.

Nice to Have:

  • Experience with cloud-based technologies.
  • Knowledge of data governance tools and data cataloguing concepts.
  • Exposure to DevOps/MLOps practices.

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