Back
Popular mid-level data engineer title, metro hiring, and known fintech brand increase applicant competition.
Core data engineering skills (SQL, Python, ETL) are broadly transferable across industries despite fintech nuances.
Explicit 2–4 years requirement plus mandatory SQL/Python and PySpark/AWS skills filter candidates moderately strictly.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, implement, and maintain scalable data pipelines collaborating with data scientists and analysts.
Ensure data quality, integrity, security, and compliance throughout data ingestion, transformation, and lifecycle.
Automate workflows and production pipelines to improve operational efficiency.
2-4 years of experience in data engineering or related field.
Proficiency in SQL and Python.
Experience with PySpark, AWS, and Snowflake is a strong plus but not strictly mandatory.
Work Experience Required: 2-4 years in data engineering or related field.
Experienced in building scalable data pipelines in collaboration with data science teams.
Competent in data validation, quality assurance, and managing multiple priorities independently.
Familiar with cloud technologies like AWS and modern data platforms such as Snowflake and PySpark.