Data Engineer Clips / ML Data

The Role

At Medal, we’re redefining how people capture and share gameplay experiences. Every day, our platform ingests tens of thousands of hours of gameplay video—raw, unfiltered, and packed with insights. We're looking for a seasoned Data Engineer to take full ownership of our Clips / ML data infrastructure, building the next generation of scalable, real-time pipelines that power everything from user-facing discovery to machine learning research. You'll lead the architecture, operations, and performance of data systems that sit at the heart of our product, influencing everything from content indexing to model training.

If you're passionate about building petabyte-scale video pipelines, love working on low-latency systems, and are excited to help define the future of real-time gaming insights, we want to hear from you.

You Will

Architect and operate petabyte-scale ingestion pipelines that ingest ~ 50 k hours of gameplay video every day

Design automated QA guard-rails (schema validation, anomaly detection, deduplication)

Build high-performance ETL and feature-extraction jobs to process and index hundreds of millions of clips into columnar / video-native formats

Own the end-to-end data ingestion stack (desktop & mobile recorders, upload services, CDN)

Establish real-time monitoring, lineage, and “five-nines” SLAs, driving continuous improvement across storage, compute, and network layers

Partner with research and product to curate high-signal data slices, data-health metrics, and accelerate model experimentation

Champion security, privacy, and governance : implement robust RBAC, audit trails, and compliant retention policies for sensitive gameplay footage and user inputs

Mentor and uplevel engineers (including internal Medal platform talent), fostering a culture of craftsmanship, documentation, and ruthless focus on data excellence

You Need

5+ years of experience in data engineering, backend systems , or related roles. Experience with video data or ML infrastructur e is a plus.

Deep knowledge of ETL / ELT pipelines , distributed systems , and streaming data architectures (e.g., Kafka, Spark, Flink, etc.)

Strong proficiency with Python, Scala, Go , or similar languages used in data-intensive environments

Experience with cloud infrastructure (e.g., AWS, GCP) and modern data stack tools (e.g., dbt, Airflow, Parquet, Arrow)

Track record of designing systems with extreme scale and performance requirements

Deep understanding of data QA methodologies , anomaly detection, and automated testing in production systems

Passion for mentorship and team development ; able to upskill engineers and advocate for engineering excellence

A bias toward ownership, urgency , and a desire to build systems that just work , even at scale

Why Join Us

Work on cutting-edge tech and help shape the future of gaming

Passionate team that values ownership and innovation

Competitive salary, equity options, comprehensive health insurance, 401k

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