Director of Engineering scaling teams and technology for Ledgebrook’s excess and surplus insurance platform. Shaping architecture, reliability, and engineering strategy across underwriting and operational systems.
About the role
- Data Developer building scalable AWS big-data and machine-learning solutions for Triton Digital’s audio streaming audience platform. Developing pipelines, ML operations, and cloud applications with Scala, Python, Spark, and Databricks.
Responsibilities
- Develop new products/applications and enhance existing ones using Scala, Python, or other relevant technologies
- Participate in all phases of the software development lifecycle, including planning, design, coding, testing, deployment, monitoring, support, and documentation
- Use modern cloud and DevOps practices
- Write high-quality code for robust, large-scale applications
- Work with data scientists to understand models and translate complex algorithms into scalable solutions
- Manage machine learning model lifecycles, including testing, deployment, and production monitoring
- Provide observability through platforms such as Grafana
- Maintain documentation of processes and best practices
- Collaborate with Big Data developers, Data Ops, Data Science, and DevOps/SRE teams to integrate data and ML solutions into AWS infrastructure
- Contribute to a self-organized, multidisciplinary Agile team
- Work with the Product Manager and other product teams to define future organizational solutions
- Recommend and support technological choices
Requirements
- Proficient in programming languages such as Scala or Python
- Experience developing applications prioritizing high concurrency and short response times
- Mastery of data modeling and parallel processing concepts
- Solid knowledge of Big Data technologies, such as Apache Spark
- Knowledge of distributed data storage systems, such as Scylla DB and AWS data services
- Advanced knowledge of Docker and Kubernetes
- Knowledge of cloud platforms, with a strong focus on AWS
- Experience with test-driven development (TDD), CI/CD, GitHub, and GitHub Actions
- Experience designing and optimizing data processing pipelines using Airflow and Databricks workflows
- Experience in Machine Learning engineering and operations applied to Big Data
- Experience with Apache Spark for ML and Databricks
- Use of AI tools in software development
- Experience developing in Agile/Scrum environments
- At least five years of professional experience as a Big Data developer
- Strong communication skills in English; French is an asset
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