Senior Data Engineer

Senior Data Engineer

For this job we are currently only hiring candidates based in the United States.

About the team & opportunity

Ontra is seeking a Senior Data Engineer reporting to our Senior Manager, Data Engineering on our Data Team.

This role is a great opportunity for someone excited to create and own a data engineering roadmap and continue to develop foundational data engineering practices at Ontra. Collaborating with product and engineering teams, you will translate other teams’ requirements into actionable engineering solutions with a focus on rapid iteration. A successful Senior Data Engineer will communicate effectively, both written and verbal, with engineers and business stakeholders.

If you are passionate about data, especially data architecture and modeling, we’d love to get to know you!

What you’ll do

  • Deliver solutions with impact for our product teams and end-users while establishing frameworks to boost efficiency of data teams
  • Architect and design strong dimensional models to support our rapidly growing analytics infrastructure
  • Build data processing pipelines and infrastructure in support of product, analytics and ML initiatives
  • Create a data engineering roadmap, taking end-to-end ownership of technical initiatives and prioritizing for impact on objectives and key results
  • Collaborate cross-functionally to lead data efforts and work proactively with stakeholders to translate data insights into product features

What you’ll bring

  • Experience: 5+ years core data engineering experience, including data modeling, data infrastructure, event logging, and infrastructure. Specific technical experience with Snowflake, dbt, Airflow, Kubernetes, Docker, DataDog and AWS are a bonus!
  • Databases: Strong understanding of using SQL and Python to build great data warehouses, with the ability to follow engineering best practices with minimal guidance
  • Collaborative: Excellent communication with technical and nontechnical stakeholders, and proactively shares knowledge across functions to generate outcomes
  • Data Driven: Looks at data to drive a path forward in technical design of data infrastructure
  • Curious: Constantly researches new data engineering and driven to grow technically
  • Problem Solving: Works well in ambiguous situations, excited to identify problems and provide solutions, even when first-order scientific approaches fail
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