Senior Data Engineer
Lead design and scaling of data pipelines and analytics infrastructure using Airflow, dbt, Python, and AWS. Requires 8+ years building production data systems and strong SQL/Python skills.
What You’ll Be Doing
- Design and lead development of scalable data pipelines using Airflow, dbt, and Python.
- Guide architecture and evolution of the company data platform.
- Build integrations across modern data stack tools including Fivetran, Redshift, and Sigma.
- Develop serverless data services using AWS services such as Lambda.
- Partner with stakeholders to define reliable data models and analytics datasets.
- Improve pipeline reliability through testing, monitoring, and observability.
- Modernize legacy data processes and improve automation across the platform.
- Mentor engineers and analysts on data modeling and platform best practices.
- Drive improvements in data governance and documentation.
What You’ll Bring to the Team
- 8+ years of experience building production data pipelines and analytics infrastructure.
- Strong SQL skills and experience modeling large datasets.
- Strong Python experience for building pipelines and automation.
- Experience with Airflow, dbt, or similar orchestration and transformation tools.
- Experience with modern data stack tools such as Fivetran, Redshift, or Sigma.
- Experience with AWS and serverless data processing such as Lambda.
- Strong understanding of data warehouse architecture and analytics engineering.
- Demonstrated ability to lead technical initiatives across teams.
Sr. Data Engineer
Design and maintain scalable data pipelines and lake architecture on GCP/AWS to power analytics, trading tools, and ML initiatives. Requires 5+ years experience, strong SQL/Python, dbt, orchestration tools, and cloud infrastructure experience.
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Own and evolve streaming data pipelines and feature stores powering real-time ML inference and model serving at Kraken. Requires 5+ years data engineering experience with 2+ years in production streaming systems.