Senior Data Engineer
Onit
About the job
About Us
We're reimagining how enterprise security teams operate in an AI-first world, transforming weeks of manual work into intelligent, automated workflows. Backed by tier-1 VCs, with second-time founders who've successfully built and sold cybersecurity companies, we're on a mission to empower security professionals to focus on strategic, high-impact work while AI handles the rest. If you're passionate about building the future of enterprise security, we want to hear from you.
About the Role
We are seeking a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and infrastructure for our platform. The ideal candidate will have extensive experience with ETL/ELT processes, analytical databases, and workflow orchestration. You will work on high-volume security data processing, building the data backbone that powers our AI-driven security platform. You will collaborate closely with Data Scientists, Security Researchers, and Full-stack Engineers.
Responsibilities
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Design and build end-to-end data pipelines that ingest high-volume security data from multiple third-party sources, transform and normalize raw connector data into deduplicated schemas with memory-efficient stream processing, and orchestrate complex workflows across multi-tenant environments.
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Write complex analytical SQL including aggregations, window functions, CTEs, and materialized views.
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Manage database schemas across both an application data database and OLAP database, including migrations and cross-database federation.
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Optimize stream processing pipelines to handle high-volume data ingestion with memory efficiency.
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Apply best practices for data governance, security, and compliance including multi-tenant data isolation patterns, while continuously monitoring and optimizing pipeline performance for cost efficiency and reliability.
Requirements
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5+ years of experience in data engineering or a similar role.
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Strong proficiency in TypeScript/Node.js for building data pipeline code.
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Expertise in OLAP databases such as Snowflake, BigQuery, Redshift, ClickHouse
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Experience with relational databases schema design and migrations such as Aurora PostgreSQL
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Hands-on experience with workflow orchestration tools (Temporal, Airflow, or similar):
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Experience building ETL pipelines with streaming data transformations ( AWS Kinesis, AWS Kafka)
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Strong experience with AWS cloud services
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Proficiency in SQL for complex analytical queries.
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Knowledge of data modeling, deduplication strategies, and distributed computing concepts. (Apache Spark, dbt, Apache Parquet)
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Excellent problem-solving skills with the ability to troubleshoot complex pipeline issues.
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Knowledge of event-driven architectures and multi-tenant data isolation patterns.
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Experience with real-time data streaming and high-volume JSON processing. (Kafka Streams, AWS Kinesis Data Streams)
Nice to Haves
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Experience in the cybersecurity domain.
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Experience with ClickHouse.