Data Platform Software Engineer (Python), Data Platform - Splunk

What You’ll Get to Do

• Contribute to end-to-end system design and participate in technical and architectural decisions.

• Build, maintain, and optimize Python-based services, engineering tools, and data pipelines.

• Work with data across the full lifecycle, including data extraction, transformation and delivery.

• Develop and maintain workflow orchestration using Apache Airflow including pipeline testing, monitoring, and reliability.

• Work with Snowflake as a data platform and dbt.

• Build and maintain CI/CD pipelines, deployment processes, and environment automation.

• Containerize and deploy applications using Docker and Kubernetes.

• Actively adopt and contribute to AI-assisted engineering and testing practices, using AI to improve development workflows, automation, and engineering productivity.

• Follow and contribute to engineering standards for code quality, testing, documentation, and development best practices.

• Collaborate with engineers, data teams, and stakeholders to design and deliver reliable, scalable solutions.

What You’ll Bring

• Bachelor’s degree + 3 years of related experience, or Master’s degree + 2 years of related experience.

• Hands-on experience with Python, including OOP, error handling, REST API integrations, and clean code practices.

• Good understanding of SQL and data engineering fundamentals.

• Familiarity with AI tools and technologies, with an interest in using AI to improve engineering workflows, automate repetitive tasks, and increase developer productivity.

• Solid understanding of Git and modern software development workflows.

• Experience building or maintaining CI/CD pipelines, preferably using GitLab CI.

• Good engineering fundamentals, including system design concepts, technical documentation, and architecture diagrams.

• Strong communication and collaboration skills, including participating in code reviews and working effectively with engineers and stakeholders.

Nice to Have

• Working knowledge of AWS services, such as IAM, S3, Glue, Athena, and MWAA/Airflow.

• Experience with cloud data platforms such as Snowflake or Redshift.

• Familiarity with observability and monitoring tools such as Prometheus, Splunk, or OpenTelemetry.

• Familiarity with Docker and Kubernetes.

• Experience with Terraform for infrastructure as code (IaC).

• Experience in developer productivity engineering, including improving engineering tooling and workflows and supporting the full software development lifecycle (SDLC).