Back
Strong Tier-1 brand, mid-level generalist data role, metro location, and broad skills increase competition.
Core data engineering skills are transferable across industries despite banking domain knowledge preference.
Explicit five-plus years requirement plus mandatory PySpark, ETL, data modeling, and cloud skills increases shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build, maintain, test, and optimize scalable data architecture to support data analytics and science use cases.
Extract, transform, and load data into data platforms ensuring data quality, security, and governance.
Collaborate with technology and architecture teams to deliver cost-effective, innovative data-driven solutions aligned with bank strategy.
At least 5 years’ experience in ETL, data modelling, data warehousing, and integrating data from multiple sources with focus on performance, reliability, quality, security, and governance.
Strong expertise in Python, PySpark, and Falcon Framework for building scalable data pipelines and RESTful APIs.
Proficiency with Agile/Scrum, Git, and cloud platforms such as AWS, Azure, or GCP.
Work location: Chennai, India with workdays to be carried out in India.
Experienced data engineer skilled in large-scale data processing, with strategic understanding of data platform cost levers.
Proficient in modern code development practices and DevOps adoption including root cause analysis and issue resolution.
Able to engage proactively with diverse stakeholders and collaborate across data engineering and architecture teams within a complex financial services environment.