Data Engineer
The Data Engineer will design, build, and optimize ETL/ELT workflows, integrate data from various sources, and automate workflows using KNIME. They will also lead the design and delivery of scalable data pipelines and implement data governance and security measures.
- On-site
- Calgary, AB
- Posted Jun 5, 2026
- Apply by May 24, 2027
- 1 position
Job summary
Airswift is seeking a Data Engineer to work a 12-month contract with one of our major clients in Calgary, AB. Key Responsibilities Design, build, and optimize ETL/ELT workflows using KNIME Analytics Platform Integrate data from relational databases, APIs, and cloud storage Automate and productionize workflows using KNIME Business Hub Develop and scale data pipelines using Databricks (Apache Spark) Implement data quality checks, anonymization, and governance controls Document workflows, data pipelines, and operational processes Lead the design and delivery of scalable Databricks data pipelines using Spark, Delta Lake, and PySpark Drive Lakehouse architecture across ingestion, transformation, and curated data layers Define technical standards and best practices for batch and streaming data engineering Optimize performance and cost efficiency of Spark workloads Implement enterprise-grade data governance, security, and monitoring (e.g., access controls, catalogs) Act as a senior technical leader and mentor within the data engineering team What You Bring Post-secondary degree in Computer Science, Software Engineering, or equivalent experience 7+ years of hands-on experience in data engineering Strong experience with Databricks, Spark, and Lakehouse architectures Advanced proficiency in PySpark, Python, and SQL Advanced experience with KNIME Analytics Platform (nodes, components, workflow control) Solid understanding of data modeling and ETL/ELT best practices Experience building and supporting production-grade data pipelines at scale Exposure to cloud platforms (Azure preferred, AWS acceptable) Familiarity with DevOps / CI/CD practices for data workloads Nice to Have Experience with MLOps and deploying machine learning workloads in Databricks Familiarity with data integration tools (e.g., Azure Data Factory, HVR, or similar) Experience working in regulated or large enterprise environments Exposure to streaming data architectures (Kafka, Structured Streaming)
What you’ll do
The Data Engineer will design, build, and optimize ETL/ELT workflows, integrate data from various sources, and automate workflows using KNIME. They will also lead the design and delivery of scalable data pipelines and implement data governance and security measures.
Requirements
Candidates should have a post-secondary degree in a relevant field and at least 7 years of hands-on experience in data engineering. Strong experience with Databricks, Spark, and KNIME Analytics Platform is required, along with proficiency in Python and SQL.
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Data Engineering
- ETL
- ELT
- KNIME
- Databricks
- Apache Spark
- PySpark
- Python
- SQL
- Data Modeling
- Cloud Platforms
- DevOps
- Data Governance
- Streaming Data
- MLOps
- Data Integration
Job areas
- Technology
- Data & Analytics
- Engineering
Additional details
- Minimum education
- Bachelor’s degree
- Minimum experience
- 5+ years
- Apply by
- May 24, 2027
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available