Senior Cloud Data Architect

21 hours ago

GulshaneIqbal Town, Pakistan beBeeData Full time 1,200,000 - 1,500,000
About the Role

We are seeking an experienced Senior Data Engineer with expertise in designing and developing large-scale data architectures to join our team.

The ideal candidate will have a strong background in Python, SQL, PySpark, Azure, Databricks, Synapse, Azure Data Lake, DevOps and cloud-based large scale data applications with a passion for data quality, performance and cost optimization.

This is a remote, contract position responsible for architecting, building and maintaining the infrastructure required for data integration, storage, processing and analytics (BI, visualization and Advanced Analytics).

Responsibilities
  • Architect, design, develop, test and maintain high-performance, large-scale, complex data architectures which support data integration (batch and real-time, ETL and ELT patterns from heterogeneous data systems: APIs and platforms), storage (data lakes, warehouses, data lake houses, etc), processing, orchestration and infrastructure.
  • Contribute to detailed design, architectural discussions and customer requirements sessions.
  • Participate in the design, development and testing of big data products.
  • Construct and fine-tune Apache Spark jobs and clusters within the Databricks platform.
  • Migrate out of Azure Synapse to Azure Data Lake or other technologies.
  • Evaluate and implement best practices and design schemas that match business needs for delivering a modern analytics solution.
  • Design and implement data models and schemas that support efficient data processing and analytics.
  • Develop clear, maintainable code with automated testing using Pytest, unittest, integration tests, performance tests, regression tests, etc.
  • Evaluate, design, implement and maintain data governance solutions such as cataloging, lineage, data quality and data governance frameworks suitable for a modern analytics solution.
  • Continuously monitor and fine-tune workloads and clusters to achieve optimal performance.
  • Provide guidance and mentorship to junior team members, sharing knowledge and best practices.

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