3 months ago
Pune, IndiaStaff+
Responsibilities
- Build and maintain data architectures and pipelines for transferring and processing durable, complete, and consistent data.
- Design and implement data warehouses and data lakes that support required data volumes, velocity, and security measures.
- Develop processing and analysis algorithms suited to data complexity and volume.
- Build and deploy machine learning models in collaboration with data scientists.
- Design and implement ETL, Hadoop, and AWS components and support infrastructure and deployment pipelines.
- Lead complex assignments or teams, guide team members, advise stakeholders, and manage risk and controls.
- Collaborate across functions and communicate complex information to influence business outcomes.
Requirements
- Hands-on AWS experience with S3, EC2, Lambda, RDS, Glue, Athena, Step Functions, data pipelines, and analytical services.
- Experience with distributed computing architecture and core Hadoop components including HDFS, Spark, YARN, Hive, and Impala.
- Expertise in SQL and advanced SQL skills.
- Expertise in shell scripting and programming with Scala or Python.
- Experience with technical design for ETL, Hadoop, and AWS components.
- Ab Initio implementation on Hadoop experience is optional.
- Ability to demonstrate risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, and job-specific technical skills.
Tech Stack
Categories
Data Engineering
About Barclays
Our vision is to be the UK-centred leader in global finance. We are a diversified bank with comprehensive UK consumer, corporate and wealth and private banking franchises, a leading investment bank and a strong, specialist US consumer bank. Through these five divisions, we are working together for a better financial future for our customers, clients, and communities. For further information about Barclays, please visit home.barclays.