Job Summary

Role: Lead Python Engineer

Location: Remote, India

Experience: 7+ Years
Role Overview

We are seeking a highly skilled Data Engineer with a strong background in Databricks and a passion for data engineering. The ideal candidate will have extensive experience in designing and implementing data solutions using various technologies, including PySpark, Spark SQL and Power BI. This role requires a proactive individual who can work independently and collaboratively in a rapid-paced environment.
Key Responsibilities
- Design, develop and optimize scalable data pipelines using Python, PySpark, Spark SQL and Databricks.
- Build and manage data solutions using Azure Databricks, Delta Lake, Unity Catalog and Databricks Workflows.
- Develop complex SQL queries, views, data models and semantic layers for data warehousing and visualization.
- Integrate and manage data using Azure Data Lake, Azure Data Factory and other Azure services.
- Develop and maintain Power BI solutions, including dashboards, DAX measures and Power Query transformations.
- Implement data governance,



security, compliance and data management best practices.
- Participate in code reviews, CI/CD processes, Agile ceremonies and end-to-end SDLC activities.
- Collaborate with cross-functional teams to understand business requirements and translate them into effective technical solutions.
Required Skills and Qualifications
- 7+ years of hands-on experience in software development, with a strong emphasis on Python programming.
- Deep expertise in PySpark (Spark SQL, DataFrames and Datasets) for building and optimizing scalable data pipelines. (PySpark)
- Solid experience with Azure Databricks (Unity Catalog), including working with Delta tables, workflows and scripting in Python.
- Understanding of data governance, data management, security and compliance in cloud environments.
- Familiar with Azure cloud services, especially Azure Data Lake, Azure Data Factory,
- Experience with Power BI, including DA

📌 Lead Python Engineer (Noida)
🏢 Algoworks
📍 Noida