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Mid-level Big Data role in metro with common PySpark/cloud skills increases candidate competition.
Low because PySpark, cloud, SQL and warehousing skills are broadly transferable across industries.
High due to explicit 4–7 years requirement, mandatory PySpark/cloud/data engineering skills, and degree requirement.
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Lead design, development and optimization of ETL/ELT data pipelines using PySpark, Python, and SQL.
Architect and implement scalable cloud-based data warehouse solutions on AWS, Azure, or GCP.
Mentor junior engineers, ensure data quality and governance, and drive performance tuning and cost optimization of data workflows.
4–7 years of experience in data engineering focused on cloud-based data solutions.
Proficiency in Python, PySpark, SQL, and experience with cloud platforms (AWS, Azure, or GCP) data services.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Location requirement: Bangalore or Pune.
Experienced in designing and optimizing scalable data architectures in a cloud-native environment.
Capable of leading cross-functional collaborations and mentoring junior engineers in best practices.
Skilled in using orchestration tools like Apache Airflow and integrating in-house data tools within agile development processes.