Python Data Engineer

2 weeks ago


Hyderabad, India Space Inventive Full time

Job description

Space is an innovative and dynamic company that specializes in leading businesses through transformative journeys in the digital era. They are pioneers in driving innovation and helping organizations transition into digitally mature entities. With a wide range of cutting-edge services, including web enterprise application development, AI & ML development, cloud engineering, data engineering, and business intelligence, Space crafts tailor-made solutions to meet each client's unique challenges. Their integrated approach combines strategic vision with digital expertise, empowering businesses to create new models, modernize legacy systems, and launch market-ready digital products and platforms.

 

Experience : 3+ years

Employment type : Permanent, Full-Time


Key Responsibilities:

  • Design, develop, and maintain efficient and scalable data pipelines for ingestion, processing, and transformation of large datasets.
  • Write clean, maintainable, and efficient Python code for data processing tasks, leveraging libraries such as NumPy and Pandas for data manipulation.
  • Develop, optimize, and troubleshoot complex SQL queries for data extraction, transformation, and analysis.
  • Utilize PySpark for distributed data processing, ensuring efficiency with large datasets.
  • Automate data workflows and optimize ETL processes to improve performance and reliability.
  • Integrate data from multiple sources (structured and unstructured) and ensure data quality and consistency.


Qualifications:

  • Proven experience as a Data Engineer or similar role, with a strong focus on Python, SQL, PySpark, NumPy, and Pandas.
  • Expertise in writing complex and optimized SQL queries for data transformation and analysis.
  • Strong knowledge of ETL processes, data pipeline architectures, and distributed data processing with PySpark.
  • Experience working with large-scale datasets and integrating data from multiple sources.
  • Familiarity with cloud-based data platforms like AWS, Azure, or GCP is a plus.



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