LP
Senior Databricks Architect
LinkedIn Recruiter Post
Senior Databricks Architect needed for contract role in Winnipeg, MB. Must have Azure Databricks, PySpark, and Azure DevOps expertise; onsite mandatory.
About the role
- Intermediate Data Engineer designing and building data pipelines for travel industry data management. Collaborating across teams to ensure reliable data for analytics and reporting.
Responsibilities
- Design, develop, and maintain robust ETL/ELT pipelines to integrate data from multiple sources into a centralized cloud-based data platform
- Build scalable data ingestion, transformation, and enrichment processes using Python, SQL, and PySpark
- Optimize data workflows for performance, scalability, and cost efficiency in the cloud
- Implement data quality and validation checks to ensure trust in reporting, analytics, and data-driven products
- Collaborate with cross-functional teams to translate business requirements into technical data solutions
- Support large-scale transformations using distributed processing frameworks
- Troubleshoot and resolve issues in data pipelines, ensuring reliability and uptime
- Participate in code reviews and contribute to engineering standards and best practices
- Document data processes, pipelines, and schemas to improve transparency and reusability
- Stay current with modern data engineering tools, practices, and cloud technologies, with a passion for continual learning and knowledge sharing
- Build with stakeholders in mind, not just raw pipelines.
Requirements
- 3+ years of experience in data engineering, data development, or data management
- Strong hands-on experience with Snowflake and modern data warehouse concepts (data lakes, lakehouse, streaming)
- Proficiency in Python and SQL for building and optimizing data pipelines
- Hands-on experience with AWS services such as S3, Glue, Lambda, Redshift, and data platforms such as Snowflake
- Experience with ETL/ELT, data modeling, and data warehousing concepts
- Experience with orchestration tools (Airflow, Dagster)
- Hands-on experience with PySpark and distributed data processing frameworks (e.g., AWS EMR)
- Knowledge of pipeline performance optimization and debugging
- Strong problem-solving, analytical, and collaboration skills
- Experience with version control (Git) and CI/CD workflows
Benefits
- RRSP matching
- Comprehensive health plans
- Flexible paid time off
- Travel experience perk
- Annual wellness perk
- Commuter perk
- Tenure-based Work From Anywhere program
- Parental leave top-up
- Adventure Pass
- Learning allowance
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