30 days ago
Pune, IndiaSenior
Responsibilities
- Build and maintain data architectures and pipelines for reliable data transfer and processing.
- Design and implement secure data warehouses and data lakes for appropriate data volumes and velocity.
- Develop processing and analysis algorithms suited to data complexity and volume.
- Manage and support OpenShift and Kubernetes container platforms.
- Collaborate with data scientists to build and deploy machine learning models.
- Use AWS data services and distributed-computing technologies to deliver scalable data solutions.
- Lead or supervise team members when assigned leadership responsibilities and coordinate team resources.
- Manage operational risk, controls, policy compliance, and stakeholder communication.
Requirements
- In-depth technical knowledge and experience in the assigned area of expertise.
- Hands-on AWS experience with Databricks, S3, EC2, Lambda, RDS, Glue, Athena, data pipelines, and Step Functions.
- Knowledge of analytical services and distributed computing architecture.
- Experience with core Hadoop components including HDFS, Spark, YARN, Hive, and Impala.
- Advanced SQL skills.
- Shell scripting and Python programming experience.
- Ability to build data warehouses, data lakes, and secure, reliable data pipelines.
- Ability to collaborate with data scientists on machine learning model deployment.
- Ability to guide team members, communicate complex information, and influence stakeholders.
Tech Stack
Categories
Data EngineeringDevOps
About Barclays
Barclays is a UK‑based universal bank that provides retail and commercial banking, credit cards (Barclaycard), wealth management, and investment banking to consumers, businesses, and institutions. Publicly listed in London and New York, it generates revenue from net interest income, fees, and markets activities, and operates across Europe, the Americas, the Middle East, and Asia. Founded in 1690 and headquartered in London, it serves customers through digital channels and a branch network.