What a data engineer does
A data engineer designs and maintains the systems that move data from your applications, databases and third-party tools into a central warehouse or lake where it can be analysed. The work includes building extract and load pipelines, transforming and modelling data, scheduling jobs, monitoring for failures and enforcing data quality and access rules. Analysts, data scientists and machine learning engineers all depend on this foundation.
Without solid data engineering, reports disagree, dashboards break and models are trained on incomplete information. A capable data engineer gives your organization one dependable version of the numbers. Finch screens candidates for SQL and Python depth, experience with your warehouse and orchestration tools, data modelling practices and how they monitor and fix pipeline failures, so you meet people who can build and maintain a reliable platform.
Typical responsibilities
- Build and maintain pipelines that load data from source systems
- Design data models and transformations in a warehouse or lakehouse
- Schedule, monitor and troubleshoot data jobs
- Implement data quality checks, testing and documentation
- Manage access controls and protect sensitive data
- Work with analysts and data scientists to deliver the data they need
Qualifications and credentials
- A degree or diploma in computer science, engineering, information systems or a related field
- Advanced SQL and strong Python skills
- Experience with platforms such as Snowflake, BigQuery, Redshift, Databricks or Microsoft Fabric
- Familiarity with orchestration and transformation tools such as Airflow, dbt or Azure Data Factory
- Cloud data certifications are often listed as assets
Who hires a data engineer
- Banks, insurers and fintech firms
- Retailers and e-commerce businesses
- SaaS and technology companies
- Health care and public sector organizations
- Data consulting firms
Where we recruit data engineer candidates
We fill data engineer roles for employers across Toronto and the GTA, including North York, Scarborough, Etobicoke, Vaughan, Markham, Richmond Hill, Mississauga, Brampton, Oakville, Burlington, Oshawa and Pickering, and for employers across Canada. GTA employers can meet us at our North York office by appointment.
What Finch checks before you meet a candidate
- Pipelines they have built, including data sources, tools and failure handling
- SQL, Python and data modelling depth
- Experience with your warehouse, cloud and orchestration tools
- Data quality and testing practices
- Handling of sensitive data and access controls
Interview questions to ask
- Describe a pipeline that kept failing. How did you find and fix the root cause?
- How would you load data into our warehouse from a system that has no API?
- How do you protect personal information as it moves through your pipelines?