Cloud Data Engineer

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery.

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

MAKE AN IMPACT

Key Responsibilities -

Design, develop and deploy AI/ML solutions on cloud platform(AWS)
Build and optimize data pipelines using Databricks and PySpark for large-scale data processing
Implement machine learning models and integrate them into production environments
Collaborate with data scientists and engineers to ensure scalable and efficient solutions
Monitor and maintain cloud-based ML workflows for performance and cost optimization
Maintain and support current legacy system in Unix and sql , pl/sql environment
Develop high quality, secure and scalable data pipelines using spark, Java/Scala on object storage and Hadoop
Follow MasterCard Quality Assurance and Quality Control processes
Leverage new technologies and approaches to innovating with increasingly large data sets
Work with project team to meet scheduled due dates, while identifying emerging issues and recommending solutions for problems
Perform assigned tasks and production incident independently
Contribute ideas to help ensure that required standards and processes are in place and actively look for opportunities to enhance standards and improve process efficiency

All About You
Hands-on experience with cloud platform(AWS) for AI/ML workloads.
Strong proficiency in Python and PySpark for data engineering and ML tasks.
Solid understanding of Databricks for big data processing and ML model deployment.
Knowledge of data architecture, distributed computing and performance tuning.
Familiarity with CI/CD pipelines for ML models.
Should have experience of working in Unix environment
Experience in Data Engineering and implementing multiple end-to-end DW projects in Big Data environment
Experience of building data pipelines through Spark with Java/Scala on Hadoop or Object storage
Experience of working with Databases like Oracle, Netezza and have strong SQL knowledge
Experience of working on Nifi will be an added advantage
Experience of working with APIs will be an added advantage
Understanding of containerization (Docker, Kubernetes) added advantage
Experience of working in Agile teams
Strong analytical skills required for debugging production issues, providing root cause and implementing mitigation plan
Strong communication skills - both verbal and written – and strong relationship, collaboration skills and organizational skills
Ability to multi-task across multiple projects, interface with external / internal resources and provide technical leadership to junior team members
Ability to be high-energy, detail-oriented, proactive and able to function under pressure in an independent environment along with a high degree of initiative and self-motivation to drive results
Ability to quickly learn and implement new technologies, and perform POC to explore best solution for the problem statement
Flexibility to work as a member of a matrix based diverse and geographically distributed project teams