Back
Tier-1 employer, metro location, and generalist senior data engineer role increase candidate competition.
Core data engineering skills (AWS, PySpark, SQL) are broadly transferable across industries.
Explicit 8–13 years plus mandatory PySpark, cloud and ETL skills yields highly selective shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and optimize scalable data pipelines and platforms primarily on AWS cloud.
Own end-to-end data pipeline projects including scope, timeline, risk management, and deployment.
Collaborate with data analysts, scientists, and business stakeholders to fulfill data requirements and ensure data quality.
8 to 13 years of relevant work experience in data engineering.
Bachelor’s degree in Computer Science, Engineering, or related field.
Hands-on experience with cloud platforms (AWS preferred), Python, PySpark, SQL, and Big Data ETL performance tuning.
No explicit notice period mentioned.
Experienced in architecting and implementing cost-effective, scalable cloud data solutions, preferably on AWS.
Capable of managing complex data challenges and mentoring junior engineers through leadership in pipeline development.
Familiarity with data engineering best practices including version control, CI/CD processes, and performance tuning for OLAP/OLTP systems.