Application & Data Engineering

About the role :

Sportz Interactive is powering the next generation of sports experiences through real-time data at scale. We are looking for a technical leader who can seamlessly blend application development with data engineering to drive our next-generation Client-facing Data Feeds Platform. You will own the end-to-end design, implementation, and operations of real-time and batch data pipelines—ingesting, transforming, and distributing large-scale sports data to downstream systems.

This role demands a deep understanding of backend systems, data architecture, and the ability to lead a team in building robust, scalable, and maintainable platforms that meet both product and performance needs. You’ll lead a team of engineers to architect clean data flows, optimize processing frameworks, and build interfaces that power data-rich applications across fantasy sports, broadcast, and digital platforms. This is a critical, hands-on role with the opportunity to shape the future of our data infrastructure. 

Key Responsibilities

• Architect and develop microservices for data ingestion, enrichment, validation, and distribution.
• Design, build, and optimize high-throughput ETL pipelines for both real-time and batch workloads, handling sports event data, telemetry, and more.
• Lead data modeling and schema design across Postgres and other RDBMS/NoSQL systems to support both OLTP and OLAP use cases.
• Implement data engineering best practices—including version-controlled pipelines, lineage tracking, and modular data transformations.
• Leverage Big Data and distributed processing frameworks where required to ensure scalable and performant systems.
• Define and implement caching strategies (Redis clusters, pub/sub, TTLs) to enable low-latency access to time-sensitive data 
• Set up and manage CI/CD pipelines, monitoring, and alerting for high-availability, production-grade systems.
• Lead and mentor a team of engineers, define technical roadmaps, coding standards, and best practices.

Background and Experience 

• 10+ years of experience in backend and/or data engineering, with at least 3 years in a technical leadership role.
• Strong expertise in Postgres or similar RDBMS: DDL/DML, schema evolution, query optimization, indexing, partitioning, replication.
• Solid grasp of data modeling principles and hands-on experience designing scalable schemas for both transactional and analytical systems.
• Proficiency in ETL/ELT design, pipeline orchestration, and performance tuning.
• Hands-on experience with Redis (clustering, persistence, pub/sub).
• Proven track record of building enterprise-grade, highly available distributed services.
• Proficiency in at least one backend language: Node.js (Preferred) , Java, Python or Go.

Good to Have

• Familiarity with message buses (Kafka, RabbitMQ) and streaming platforms (Kinesis, Flink, Spark Streaming).
• Exposure to Cloud-based RDBMS (AWS RDS/Aurora, GCP CloudSQL, etc.)
• Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• Understanding of data governance, data quality frameworks, and lineage tracking.