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Staff Data Engineer

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Description

  • Platform Evolution: Lead the design and evolution of our modern data platform architecture, ensuring it remains scalable, available, and performant
  • Pattern Implementation: Apply in-depth knowledge of advanced architectural patterns—such as Event Driven, CQRS, event sourcing, and Saga patterns—to solve complex data challenges
  • Technical Governance: Develop, document, and communicate standard methods and processes to be utilized within our technology stack, including dbt, Airflow, Snowflake, Kafka, and traditional ETL
  • Strategic Collaboration: Act as a key partner to senior leadership on strategic data projects and build strong working relationships with other IT leaders by providing technical acumen and thought leadership
  • Enterprise-Scale Infrastructure: Architect and manage enterprise-scale data platforms while setting best practices for development teams, including security, privacy, monitoring & alerting, and CI/CD
  • Advanced Data Modeling: Implement sophisticated data modeling strategies, including Kimball, Inmon, or Data Vault, and drive the transition toward modern concepts like Data Mesh
  • Complex Problem Solving: Provide solutions for complex business problems, enabling insights that can empower better decision-making across the organization
  • Operational Excellence: Set and enforce best practices for the full software development and technology management life cycle, including coding standards, code reviews, source control management, and testing
  • Culture of Excellence: Take an active role in fostering a culture of learning and excellence within the engineering organization
  • Influence through Data: Leverage data to prioritize work and influence others across the organization
  • Change Management: Proactively implement change and improvements when seeing opportunities to optimize the platform or processes
  • Current Technologies Being Used Today:
  • Data Warehouse: Snowflake, Oracle, MySQL
  • Transformation: dbt (data build tool)
  • Orchestration: Apache Airflow
  • Programming: Python, SQL
  • Streaming: Kafka
  • Cloud: AWS (S3, EMR, Glue)
  • Infrastructure: Terraform

Benefits

  • Remote/hybrid flexibility
  • Parental leave
  • Wellness allowance
  • Career development paths
  • Stock purchase program
  • Immediate 401(k) matching
  • Mental health support
  • FSA/HSA options
  • Life insurance
  • 20 days PTO from day one, plus 10 paid holidays annually
  • Leadership training, mentorship programs, education reimbursement & industry certifications
  • Performance bonuses & annual merit increases
  • Premium health coverage, plus dental & vision
  • Education: Bachelor’s degree in Computer Science, Computer Engineering, or a related technical discipline
  • Experience: 7+ years of relevant professional engineering experience, with a proven track record of building and operating large-scale distributed systems
  • Communication: Excellent verbal and written communication skills with an interest in continuous learning and improvement
  • Data Engineering: Strong data engineering background working with dbt, Snowflake, Kafka, and cloud-based services (AWS S3, EMR, Glue)
  • Infrastructure & Tooling: Hands-on experience with Terraform, Airflow, Tableau, MySQL, and Oracle
  • Software Engineering: Deep knowledge of professional software engineering practices for the full technology management life cycle; experience with Agile is preferred
  • Job Application Deadline: 09/30/2026

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