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Tier-1 brand, metro location, generalist data engineer role with broad skill requirements.
Core data engineering skills (Python, PySpark, cloud) are highly transferable across industries.
Explicit 8–13 years requirement plus mandatory cloud, PySpark, ETL, and SQL skills increases shortlisting strictness.
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Design, build, and optimize end-to-end scalable data pipelines and platforms using cloud technologies (AWS preferred).
Own the full lifecycle of data pipeline projects including scope, timelines, risk management, and deployment.
Ensure data quality and integrity via testing and monitoring, while mentoring junior engineers and collaborating with analysts, data scientists, and business stakeholders.
8 to 13 years of work experience in data engineering or related fields.
Bachelor’s degree in Computer Science and Engineering preferred; other engineering fields considered.
Hands-on experience with cloud platforms (AWS, Azure, GCP) and proficiency in Python, PySpark, and SQL.
Work Experience Required: 8 to 13 years
Experienced in architecting cost-effective, scalable data solutions on cloud platforms, especially AWS.
Strong problem-solving skills in big data ETL performance tuning and data pipeline challenges.
Familiar with software engineering best practices (CI/CD, version control, automated testing) and tools like Apache Spark and Apache Airflow.