Data Solutions Developer

3 days ago

Aurangabad, Maharashtra, India beBeeDataSolutions Full time ₹ 15,00,000 - ₹ 25,00,000

Job Summary

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We are seeking a skilled Data Solutions Developer to join our team and contribute to the design, development, and maintenance of our data platform.

As a key member of our implementation team, you will play a crucial role in building efficient data pipelines to extract, transform, and load data from various sources into our data lake and data warehouse.

You will work closely with cross-functional teams to develop and optimize data workflows that support our analytics and reporting needs. Your expertise will be instrumental in ensuring data quality, integrity, and reliability throughout the data lifecycle.

Key Responsibilities:

  • Data Pipeline Development:
    • Design and develop data pipelines using Databricks PySpark to extract, transform, and load data from heterogeneous sources into our data lake and data warehouse.
    • Optimize data pipeline workflows for performance and scalability, leveraging Databricks PySpark and Spark SQL to efficiently process large data volumes.
    • Implement robust error handling and monitoring mechanisms to proactively detect and resolve issues within data pipelines.
    • Design and implement data solutions following the Medallion Architecture principles, organizing data into Bronze, Silver, and Gold layers.
    • Ensure data is appropriately cleansed, enriched, and optimized at each stage to support robust analytics and reporting.
  • Data Analysis and Query Optimization:
    • Write and optimize complex SQL queries for data manipulation, aggregation, and analysis within Databricks PySpark applications.

Required Skills and Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Minimum of 3 years of experience as an ETL developer, with a strong focus on Databricks PySpark development.
  • Proficiency in Python programming, with extensive experience in developing and debugging Databricks PySpark applications.
  • In-depth understanding of Spark architecture and internals, with hands-on experience in Spark RDDs, DataFrames, and Spark SQL.
  • Expertise in writing and optimizing complex SQL queries for data manipulation, aggregation, and analysis.
  • Proven experience in working with large-scale data warehousing and ETL frameworks.
  • Strong problem-solving skills and the ability to troubleshoot and resolve data pipeline issues.
  • Excellent communication and collaboration skills, with the ability to work effectively in a team environment.

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