Job Description

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 leas

t 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.