Job Title: Data Engineer - Real-Time Systems

Company Name: Impac Exploration Services

Job Details: RemoteFull,Time

Job Url: https://hiring.cafe/viewjob/mr4bak4wc1grh2z4

Job Description: Posted 7mo agoData Engineer - Real-Time Systems@ Impac Exploration ServicesView All JobsWebsiteWeatherford or Houston or San JoseRemoteFull TimeResponsibilities:Build streaming, Scale pipelines, Ensure resilienceRequirements Summary:Experience building streaming systems; real-time processing; knowledge of Kafka or similar; proficiency in Python/Java/Rust; familiarity with containers and orchestration.Technical Tools Mentioned:Apache Kafka, Pulsar, Redpanda, Flink, Spark Streaming, TimescaleDB, InfluxDB, Python, Java, Rust, Docker, Kubernetes
Data Engineer - Real-Time SystemsDivision: DATUM, Impac Exploration ServicesLocation: Remote, Oklahoma City (OK), Houston (TX), San Jose (CA)Type: Full-TimeWe're done with the "load it tonight, analyze it tomorrow" paradigm. At DATUM, decisions happen in milliseconds, not morning reports. We need a data engineer who believes streaming is the default, not the exception—someone who gets genuinely frustrated when people suggest "just run it as a nightly job."Our data doesn't wait for convenient processing windows. It flows from sensors, cameras, and systems that never sleep. Your infrastructure will catch it, process it, and serve insights before traditional pipelines even know it arrived. If you think Kafka is table stakes and real-time inference is the only kind worth doing, we should talk.What You'll BuildStreaming pipelines that handle millions of events per secondInfrastructure for real-time ML inference at the edge and coreSystems that treat historical data as streaming replay, not static filesData architectures that scaleFault-tolerant pipelines that keep flowing when hardware failsYour PhilosophyThe best data lake is a flowing riverEvery millisecond of latency is a missed opportunityStatic ETL is where good data goes to get staleIf it's not real-time, it's not realTechnical RealityCore streaming stack:Apache Kafka/Pulsar/Redpanda (or better alternatives you'll introduce)Flink/Spark Streaming for complex event processingTime-series databases that can actually keep up (TimescaleDB, InfluxDB, or custom)Languages: Python/Java/Rust—whatever makes it fastContainer orchestration without cloud vendor lock-inWhat you won't use:Traditional ETL tools that think "streaming" means every 5 minutesCloud services that hold your data hostageArchitectures that fall over when AWS hiccupsYou're Our Person IfYou've built streaming systems that stayed up when it mattered"Eventually consistent" makes you uncomfortableReal-time inference excites you more than data warehousingEspecially IfYou've built on-premise streaming infrastructure that rivals cloud offeringsYou've done inference at the edge before edge was coolYou understand hardware—from NVMe optimization to network tuningYou've migrated from batch to streaming and never looked backYou can make time-series data sing at scaleYou believe data gravity is a solvable problemWhy This MattersYour pipelines will power:ML models making decisions while drill bits are turningComputer vision processing streams from harsh environmentsAnalytics that prevent problems rather than explaining them laterSystems where "historical analysis" means 30 seconds agoThis isn't building dashboards for quarterly reviews. This is infrastructure for decisions that can't wait.Growth PathToday: Building streaming pipelines that embarrass traditional ETL  Six months: Architecting systems that make cloud vendors nervous. One year: Publishing approaches that redefine industrial data processing. When Databricks or Confluent tries to hire you, it'll be because you built something better than what they're selling.Reality CheckYou'll fight against decades of batch processing mindset. You'll optimize systems down to microseconds. You'll build infrastructure in places with challenging connectivity. You'll explain why "real-time" isn't just a buzzword.But you'll also enable genuinely new capabilities. You'll prove that industrial systems can be as responsive as trading platforms. You'll build the foundation for AI that reacts as fast as physics demands.Ready to Stream?Show us streaming systems you've built that others said were impossible. Tell us why you believe batch processing is (mostly) dead. Share your vision for data infrastructure unchained from cloud providers.We're looking for someone who sees "process nightly" and thinks "why wait?"