Senior Data Engineer at PayU Billing Solutions
Bengaluru, karnataka, India -
Full Time


Start Date

Immediate

Expiry Date

15 Aug, 26

Salary

0.0

Posted On

17 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, SQL, NoSQL, AWS, Spark, PySpark, Airflow, Debezium, Hadoop, ETL/ELT, Data Modeling, Data Warehouse Design, Distributed Computing, ML Model Deployment, Feature Store Architecture, Query Optimization

Industry

Financial Services

Description
About the Team  Our Data Engineering team is a dynamic and innovative group that forms the backbone of our data-driven organization. We are responsible for building and maintaining robust, scalable data infrastructure that powers critical business decisions across multiple domains. The team works on cutting-edge technologies and handles massive data volumes, ensuring seamless data flow from various sources to our data warehouse and analytics platforms. We play a crucial role in powering Machine Learning models across various use cases by building sophisticated feature engineering pipelines, deploying ML model infrastructure, and maintaining real-time feature generation systems.   About the Role  As a Senior Data Engineer, you will play a crucial role in designing, implementing, and maintaining our data infrastructure. You'll work with modern data engineering technologies and cloud platforms to build scalable ETL pipelines, optimize data processing workflows, and ensure data quality and reliability across our systems. This role extends significantly into the ML domain, where you'll be responsible for building and maintaining feature engineering pipelines that power various ML models across the organization. You'll work on real-time feature generation systems, deploy and maintain ML model infrastructure, and ensure seamless integration between data pipelines and ML workflows. Your work will directly impact model performance and enable data scientists to focus on model development rather than infrastructure concerns.    Responsibilities:  Partner closely with business stakeholders to understand and translate data warehouse requirements into technical solutions  Provide comprehensive support for data warehouse initiatives including requirements gathering, solution design, and implementation  Optimize data warehouse performance through query optimization, indexing strategies, and architectural improvements  Design, develop, and maintain robust ETL/ELT pipelines using modern data engineering tools   Implement real-time and batch data processing solutions to meet business requirements   Develop and maintain data models and DataMart solutions for analytics and reporting needs  Deploy and maintain ML model infrastructure ensuring scalability and reliability      Requirements:  3-6 years of experience in Data Engineering  Strong expertise in distributed computing and advanced problem-solving/analytical skills  Deep understanding of data warehouse design, optimization, and performance tuning  Expertise in Python, SQL and NoSQL databases  In-depth experience in Could services, preferably AWS (EMR, S3, Redshift, MSK)  Expertise in Data engineering tech stack like Spark (PySpark), Airflow, Debezium, Hadoop  Experience in data modelling, DataMart development  Understanding of ML model deployment and maintenance workflows with feature store architectures and best practices  Good to Have - Experience in setting up and working with On-premises Data Engineering tech stack          What we offer?  A positive, get-things-done workplace  A dynamic, constantly evolving space (change is par for the course – important you are comfortable with this).  An inclusive environment that ensures we listen to a diverse range of voices when making decisions.  Ability to learn cutting edge concepts and innovation in an agile start-up environment with a global scale.  Access to 5000+ training courses accessible anytime/anywhere to support your growth and development (Corporate with top learning partners like Harvard, Coursera, Udacity).    About us:   At PayU, we are a global fintech investor and our vision is to build a world without financial borders where everyone can prosper. We give people in high growth markets the financial services and products they need to thrive. Our expertise in 18+ high-growth markets enables us to extend the reach of financial services. This drives everything we do, from investing in technology entrepreneurs to offering credit to underserved individuals, to helping merchants buy, sell, and operate online. Being part of Prosus, one of the largest technology investors in the world, gives us the presence and expertise to make a real impact. Find out more at www.payu.com    Our Commitment to Building A Diverse and Inclusive Workforce  As a global and multi-cultural organization with varied ethnicities thriving across locations, we realize that our responsibility towards fulfilling the D&I commitment is huge. Therefore, we continuously strive to create a diverse, inclusive, and safe environment, for all our people, communities, and customers. Our leaders are committed to create an inclusive work culture which enables transparency, flexibility, and unbiased attention to every PayUneer so they can succeed, irrespective of gender, color, or personal faith. An environment where every person feels they belong, that they are listened to, and where they are empowered to speak up. At PayU we have zero tolerance towards any form of prejudice whether a specific race, ethnicity, or of persons with disabilities, or the LGBTQ communities. 

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Responsibilities
Design and maintain scalable data infrastructure and ETL pipelines to support business analytics and data warehousing. Build and manage feature engineering pipelines and infrastructure to power machine learning models across the organization.
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