Databricks Data Engineer
- Toronto, ON
- Hybride
- Publié 18 sept. 2026
- 1 poste
57 $–59 $ / heure
Ouvre un site externe
- Type d’emploi
- Contrat
- Niveau d’expérience
- Chef d’équipe · 12+ ans
- Formation minimale
- Baccalauréat
- Postuler avant le
- 11 oct. 2026
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Présence au bureau
- 3 jours par semaine
- Niveau d’expérience
- Mid-Senior level
- Mode de candidature
- La candidature directe est offerte
Résumé du poste
The role involves designing and implementing large-scale distributed data systems and leading technical solutions in ambiguous business environments. Responsibilities include developing ETL/ELT pipelines and managing production deployments using DevOps practices.
Détails du poste
Job Title: Databricks Data Engineer Location: Toronto, ON Work Arrangement: Hybrid (3 days a week) Employment Type: Contract Duration: 06-12 Months Pay Rate: CAD 57-59/hour Incorporated Domain: BFSI Application Deadline: Sept. 30th, 2026 SKILLS REQUIRED: • 12+ years of experience in Data Engineering, Data Architecture, or large-scale distributed data systems. • Expert knowledge of AWS Data Services and Databricks/Spark ecosystem. • Strong expertise in data modeling (Dimensional, Canonical, Data Vault, Domain-Driven). • Advanced SQL and Python development skills with ETL/ELT experience. • Experience with CI/CD, GitHub, DevOps practices, automated testing, and production deployments. • Proven ability to work independently and lead solutions in ambiguous business environments. Preferred Qualifications • Experience in Asset Management, Wealth Management, or Financial Services. • Knowledge of data quality frameworks, metadata management, dbt, semantic layers, or data mesh concepts. • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience). EEOC Compliance: We are an equal opportunity employer, and all qualified applicants will receive consideration for employment. DISCLAIMER AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.
Ce que vous ferez
The role involves designing and implementing large-scale distributed data systems and leading technical solutions in ambiguous business environments. Responsibilities include developing ETL/ELT pipelines and managing production deployments using DevOps practices.
Exigences
Candidates must have over 12 years of experience in data engineering with expert knowledge of AWS and the Databricks/Spark ecosystem. Proficiency in advanced SQL, Python, and various data modeling methodologies is required.
Compétences indiquées
- SQL · Souhaitée
- GitHub · Souhaitée
- CI/CD · Souhaitée
- Tests automatisés · Souhaitée
- Asset Management · Souhaitée
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Data Engineering
- Data Architecture
- AWS Data Services
- Databricks
- Apache Spark
- Data Modeling
- SQL
- Python
- ETL/ELT
- CI/CD
- GitHub
- DevOps
- Automated Testing
- Production Deployments
- Asset Management
- Wealth Management
Domaines d’emploi
- Data & Analytics
- Technology
- Software
- Engineering
- Finance & Accounting
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