Author comprehensive technical design documents to propose, evaluate, and implement scalable infrastructure and tooling solutions.
Build intuitive internal CLI tools, web applications, and Python-based SDKs leveraging Ray.
Architect, deploy, and maintain robust cloud infrastructure on AWS.
Leverage modern data tooling and formats (dbt, Apache Iceberg / Parquet, Redshift) to build highly efficient data pipelines.
Champion continuous integration and deployment best practices using GitLab, while deploying scalable services and workloads.
Act as a technical pillar on the team, establishing standards and mentoring peers.

Requirements

5+ years of software engineering experience, with a strong focus on backend, data infrastructure, or platform engineering.
Deep expertise in Python, particularly in building scalable backend systems, SDKs, and CLI tools.
Proven experience working within AWS, data warehouses like Redshift, and open-source data formats like Iceberg and Parquet.
Experience working with DBT for data transformations and interacting with BI platforms like Looker.
Hands-on experience with Ray for scaling Python workloads.
Strong familiarity with containerization (Docker/Kubernetes) and setting up robust CI/CD pipelines via GitLab.
Demonstrated ability to write clear, concise, and thorough technical design documents and lead architecture reviews.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonAWSdbtApache IcebergParquetRedshiftRayDockerKubernetesCI/CD

Soft Skills

mentoringtechnical documentationleadership