Builds and optimizes big data pipelines processing billions of signals for technographic data services. Requires 5+ years experience with Spark, Hadoop, Java/Scala, and distributed systems; collaborates with data scientists on ML integration.
112k – 176k
Hybrid5+ YOEData Engineering
About the role
What You'll Do
Build and optimize big data pipelines to extract and process signals from the web, job postings, and other sources
Design and implement data architectures and storage solutions to efficiently handle massive data volumes
Collaborate closely with data scientists to support and integrate ML models into data workflows
Continuously improve data quality, performance, and scalability of our technographic data platform
Drive technical strategy and roadmap for the data processing infrastructure
What We're Looking For
Extensive experience building and scaling big data pipelines and architectures from scratch
Deep expertise in big data frameworks (Hadoop, Spark) and the JVM stack (Java, Scala)
Strong software engineering fundamentals and ability to write efficient, high-quality code
Experience with entity recognition and NLP techniques a plus
Proven track record delivering results and driving projects in a fast-paced environment
Excellent collaboration and communication skills to work with data scientists, analysts and product teams
Passion for leveraging huge datasets to power valuable insights
Ideal Background
5+ years of experience in software engineering roles
Experience working with very large datasets and distributed systems
Familiarity building data pipelines at large tech companies or data-driven organizations
Bachelor's or advanced degree in Computer Science, Engineering or related technical field
Skills
SparkHadoopJavaScalaBig Data PipelinesDistributed SystemsNLPEntity RecognitionData ArchitecturesMl Models
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