Medal
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
#LI-DH1
#J-18808-Ljbffr
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
#LI-DH1
#J-18808-Ljbffr