Senior DevOps Engineer ( Edge, Data Engineer )
STRONG BACKEND PLATFORM : MUST HAVE A DEEP INFRA & SECURITY BACKGROUND, NOT JUST DATA ENGINEERING. ALONG WITH STRONG EDGE CONNECTIVITY EXPERIENCE
SERIOUS is rebuilding critical industry by unlocking trapped industrial data and transforming it into a central nervous system that powers mission-critical workflows — from maintenance to operations to safety. This is 0 → 1 work: building the industrial OS of the future that connects every data point, decision, and process into one intelligent platform.
What you've done
• Built heavy data pipelines and ETL systems in production — terabytes of streaming and batch data, strict requirements on correctness, latency, and time alignment
• Worked with messy real-world data sources: industrial sensors, time series, video, audio, LiDAR, geospatial — not just clean relational tables
• Owned infrastructure and DevOps at a startup. CI/CD, IaC, containers, keeping production running. You were the person on call
• Done hands-on security engineering. Threat modeling, secrets management, network segmentation, compliance — not as a checklist but because the systems you built required it
• Been an early hire or first engineer somewhere and built something from scratch that went to production and stayed there
What you'll own
• Data pipeline architecture from edge sensors through ingestion, transformation, fusion, and delivery into analytics and AI workloads — including multimodal sources like video, audio, and LiDAR alongside traditional telemetry
• ETL tooling with versioning, orchestration, and data quality enforcement so new sources can be onboarded without rebuilding from scratch every time
• Streaming and real-time infrastructure including event-driven systems, edge-to-cloud sync, offline buffering, and latency guarantees set by operational physics
• All DevOps: CI/CD, IaC, container orchestration, edge deployment, cloud GPU provisioning
• Security across the stack: hardening, access control, secrets, scanning, audit logging, and compliance for systems that run mission-critical industrial operations
• Observability and production ops for a distributed system spanning cloud, edge, and enterprise integrations
Who you are
• Strong across data engineering, DevOps, and security — you've actually done all three, not just listed them on a resume
• Experienced with Kafka, Spark, Flink, Airflow, dbt, or equivalent and pragmatic about tool selection
• Comfortable with data that doesn't come in neat rows — sensor streams, point clouds, video, time series
• Think about security as part of system design, not something you add later
• Care about data quality, schema discipline, and pipeline reliability because you've been burned when those things slip
• Want to own something fully and build it right. Not looking for a job — looking for the thing you pour yourself into for the next several years
Industry
• Data Infrastructure and Analytics
Employment Type
Full-time
Apply Now
Apply Now
SERIOUS is rebuilding critical industry by unlocking trapped industrial data and transforming it into a central nervous system that powers mission-critical workflows — from maintenance to operations to safety. This is 0 → 1 work: building the industrial OS of the future that connects every data point, decision, and process into one intelligent platform.
What you've done
• Built heavy data pipelines and ETL systems in production — terabytes of streaming and batch data, strict requirements on correctness, latency, and time alignment
• Worked with messy real-world data sources: industrial sensors, time series, video, audio, LiDAR, geospatial — not just clean relational tables
• Owned infrastructure and DevOps at a startup. CI/CD, IaC, containers, keeping production running. You were the person on call
• Done hands-on security engineering. Threat modeling, secrets management, network segmentation, compliance — not as a checklist but because the systems you built required it
• Been an early hire or first engineer somewhere and built something from scratch that went to production and stayed there
What you'll own
• Data pipeline architecture from edge sensors through ingestion, transformation, fusion, and delivery into analytics and AI workloads — including multimodal sources like video, audio, and LiDAR alongside traditional telemetry
• ETL tooling with versioning, orchestration, and data quality enforcement so new sources can be onboarded without rebuilding from scratch every time
• Streaming and real-time infrastructure including event-driven systems, edge-to-cloud sync, offline buffering, and latency guarantees set by operational physics
• All DevOps: CI/CD, IaC, container orchestration, edge deployment, cloud GPU provisioning
• Security across the stack: hardening, access control, secrets, scanning, audit logging, and compliance for systems that run mission-critical industrial operations
• Observability and production ops for a distributed system spanning cloud, edge, and enterprise integrations
Who you are
• Strong across data engineering, DevOps, and security — you've actually done all three, not just listed them on a resume
• Experienced with Kafka, Spark, Flink, Airflow, dbt, or equivalent and pragmatic about tool selection
• Comfortable with data that doesn't come in neat rows — sensor streams, point clouds, video, time series
• Think about security as part of system design, not something you add later
• Care about data quality, schema discipline, and pipeline reliability because you've been burned when those things slip
• Want to own something fully and build it right. Not looking for a job — looking for the thing you pour yourself into for the next several years
Industry
• Data Infrastructure and Analytics
Employment Type
Full-time
Apply Now
Apply Now