Posted 5 days ago
Data Engineer
@ TechDoQuest
Toronto, Ontario
Overview
TechDoQuest is hiring a Data Implementation Engineer in Toronto on a 6-12 month contract, renewable based on performance and requirements. The role builds and maintains scalable data pipelines and architectures for large financial datasets using Snowflake, Spark, PySpark, Azure and Python. The posting requires hybrid work with 3 days per week at the client office in Ethoca's Toronto office.
Responsibilities:
- Design, build and maintain scalable data pipelines
- Implement data architectures for large financial datasets
- Write maintainable Python and SQL code
- Integrate data governance and lineage tracking
Requirements summary:
- 4+ years of data engineering experience
- Advanced SQL and relational and NoSQL databases
- Snowflake, Hadoop, Spark, PySpark, Databricks, Azure
- Python proficiency for data engineering
- Familiarity with orchestration and workflow tools
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-11-10
- First seen by our source
- 2026-11-14
- Source record updated
- 2026-11-14
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Experience | 4+ years |
| Hours per week | 40 (estimated) |
| Travel | air: none · ground: none |
| Work setting | Office, Client sites |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
TechDoQuest
| Field | Value |
|---|---|
| Open jobs on Jobsy | 27 |
Title: Data Implementation Engineer
Location: Toronto, Canada
Duration: 6-12 months and then keep renewing based on performance/requirements
Hybrid 3 days from client office in Ethoca office
Key Skills: Snowflake, PySpark, Azure, DevOps
Domain: BFSI preferred
Skills & Qualifications:
4+ years of Data Engineering experience
Advanced SQL; experience with relational and NoSQL databases
Strong experience with Snowflake, Hadoop, Spark, PySpark, Databricks, Azure
Proficiency in Python for data engineering
Familiarity with orchestration tools and workflow management systems
Responsibilities:
Design, build, and maintain scalable data pipelines using Snowflake, Hadoop, Spark, PySpark, Azure
Implement data architectures and optimize workflows for large financial datasets
Write high-quality, maintainable Python and SQL code following best practices
Integrate data governance, metadata management, and lineage tracking into solutions
This job is open for fulltime as well.
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