Senior Data Engineer
About the Team
Our Data Engineering team is the backbone of PayU’s data-driven organization. We design, build, and operate scalable data platforms that support critical business decisions across multiple domains.
Working with large and diverse data volumes, the team enables reliable data movement from operational systems to data warehouses, data lakes, lakehouses, and analytics platforms. We collaborate closely with business and technology stakeholders to build fit-for-purpose data solutions that address evolving organizational needs.
About the Role
As a Senior Data Engineer, you will design, develop, and maintain scalable data infrastructure and processing solutions. You will work across batch and real-time data platforms, optimize data workflows, and help ensure the performance, quality, reliability, and accessibility of enterprise data.
The role offers an opportunity to work with modern cloud and open-source technologies while contributing to the development of data warehouse, lakehouse, and analytical serving platforms.
Key Responsibilities
- Partner with business and technology stakeholders to understand data requirements and translate them into scalable technical solutions.
- Lead requirements gathering, solution design, development, implementation, and support for data warehouse and data platform initiatives.
- Design, develop, and maintain reliable ETL and ELT pipelines using modern data engineering technologies.
- Build and optimize batch and real-time data processing solutions.
- Design and maintain data models, analytical datasets, and DataMart solutions for reporting and business intelligence.
- Improve data warehouse performance through query optimization, partitioning, indexing strategies, workload management, and architectural improvements.
- Develop data lakehouse solutions using technologies such as Apache Iceberg, Apache Spark, Apache Flink, Debezium, Apache Kafka, and Apache Airflow.
- Build and maintain low-latency data serving and query platforms using technologies such as Trino, StarRocks, and ClickHouse.
- Develop customized data solutions in collaboration with stakeholders across the organization.
- Implement data quality, validation, monitoring, observability, and reliability practices across data pipelines and platforms.
- Troubleshoot production issues, perform root-cause analysis, and drive continuous improvements in data platform performance and stability.
- Contribute to engineering standards, documentation, code reviews, and best practices.
Required Qualifications and Experience
- 3–6 years of professional experience in Data Engineering or a related discipline.
- Strong programming and analytical skills, with expertise in Python and SQL.
- Strong understanding of distributed systems, data processing, and large-scale data architectures.
- Hands-on experience designing and optimizing data warehouses, data lakes, or lakehouse platforms.
- Experience with data modeling, dimensional modeling, and DataMart development.
- Experience building and operating batch and streaming data pipelines.
- Strong understanding of query optimization, performance tuning, data partitioning, and workload management.
- Experience working with relational and NoSQL databases.
- Hands-on experience with cloud platforms, preferably AWS, including services such as:
- Amazon S3
- Amazon EMR
- Amazon Redshift
- Amazon MSK
- Practical experience with several technologies from the following ecosystem:
- Apache Spark / PySpark
- Apache Airflow
- Apache Kafka
- Debezium
- Apache Flink
- Apache Iceberg
- Trino
- StarRocks
- ClickHouse
- Hadoop
- Experience working in Agile or fast-paced technology environments.
- Strong communication and stakeholder-management skills.
Good to Have
- Experience designing or operating on-premises data engineering platforms.
- Experience with CDC, database replication, and incremental data processing.
- Experience with data quality frameworks, monitoring, and pipeline observability.
- Experience deploying data platforms using containers and Kubernetes.
- Familiarity with infrastructure automation and DevOps practices.
What We Offer
- A positive, collaborative, and get-things-done workplace.
- A dynamic and constantly evolving environment where adaptability is valued.
- An inclusive culture that encourages diverse perspectives and open communication.
- Opportunities to work on cutting-edge data technologies at global scale.
- The opportunity to learn and innovate in an agile fintech environment.
- Access to 5,000+ training courses available anytime and anywhere through leading learning partners such as Harvard, Coursera, and Udacity.
About PayU
At PayU, we are a global fintech investor with a vision to build a world without financial borders, where everyone can prosper. We provide people in high-growth markets with the financial services and products they need to thrive.
Our expertise across 18+ high-growth markets enables us to expand access to financial services. This drives everything we do—from investing in technology entrepreneurs and offering credit to underserved individuals, to helping merchants buy, sell, and operate online.
As part of Prosus, one of the world’s largest technology investors, PayU combines global reach, deep expertise, and the ability to create meaningful impact. Learn more at **www.payu.com**.
Our Commitment to Diversity and Inclusion
PayU is committed to building a diverse, inclusive, and safe workplace where every individual feels respected, valued, heard, and empowered to succeed.
As a global, multicultural organization, we welcome people from diverse backgrounds, identities, experiences, and perspectives. Our leaders are committed to fostering a transparent, flexible, and equitable work culture where everyone has the opportunity to grow and contribute.
PayU has zero tolerance for discrimination or prejudice based on race, ethnicity, gender, color, religion, disability, sexual orientation, gender identity, or any other personal characteristic.