The Opportunity
Highspring is seeking a Bilingual Data Engineer (English & French) to support one of our Montreal-based partners in designing, building, and optimizing modern data pipelines. This role is ideal for someone who excels in Python development, brings hands-on Databricks expertise, and thrives in dynamic, cloud-driven environments.
What You'll Do
- Design, develop, and optimize scalable data pipelines and ETL processes using Python and Databricks
- Implement robust data ingestion, transformation, and integration workflows across structured and unstructured sources
- Collaborate with data architects, analysts, and business teams to understand data requirements and deliver high-quality solutions
- Build and maintain reusable, well-documented code aligned with engineering best practices
- Monitor, troubleshoot, and enhance data pipelines to ensure reliability and performance
- Contribute to data governance, quality standards, and security compliance
- Participate in Agile ceremonies and provide technical insights to improve overall delivery
What You Bring to the Table
Proven experience as a Data Engineer in a cloud or modern data ecosystemStrong programming skills with Python , including testing, packaging, and version controlHands-on expertise with Databricks , including Spark-based pipelines and Delta LakeFamiliarity with cloud platforms (Azure, AWS, or GCP)Strong communication skills in both English and FrenchAbility to work in a collaborative consulting environment supporting client-facing projectsCore Skills Required
Databricks / SparkSQL and relational / non-relational data modelingVersion control (Git)Our Stack
PythonDatabricks / SparkWhy Join Highspring
Work on impactful, modern engineering projects across multiple industriesJoin a collaborative team that values innovation, curiosity, and continuous learningAccess growth opportunities, mentorship, and career development pathwaysA culture that prioritizes people, quality craftsmanship, and meaningful problem solvingDatabricks / SparkPythonDatabricks / Spark#J-18808-Ljbffr