Job Title: DataOps/Cloud Data Engineer - Senior

Location: Toronto, Ontario, Canada

Work Model: Onsite

Duration: 12 months

Extension: 1 Time

Supplier Comments

- Nice to have:
- Prior OPS/Public sector exp.
- Experience with Microsoft Purview and Microsoft Fabric

Must Haves

- Experience with Databricks, Delta Lake and Databricks SQL.
- Knowledge of Medallion Architecture.
- Experience with Azure Data Services/Azure Data Factory
- Experience with Informatica or equivalent integration platforms.
- Experience operationalizing common data models and metadata repositories.

Description / Responsibilities / Skills

Responsibilities

- Designing and developing data pipelines from source to end user
- Optimizing data pipelines

General Skills

- Experience in DataOPS principle, best practice, and implementation and Agile project development and deployment
- Experience in Continuous Integration/Continuous Development/Deployment (CI/CD) and Data provisioning Automation
- Experience with DataOPS performance monitoring and tuning
- A team player with a track record for meeting deadlines

Experience & Skill Set Requirements

General Skills (80%)

- Demonstrated experience designing, implementing and supporting cloud-based data platforms and services.
- Experience developing scalable ETL/ELT processes, data pipelines and integration solutions.
- Experience implementing DataOps practices including deployment automation, testing, monitoring and operational support.
- Experience with cloud-native data engineering and contemporary data platform architectures.




- Experience implementing metadata, lineage and data quality capabilities within cloud data environments.
- Experience developing integration solutions using APIs, event-driven architectures and batch or streaming technologies.
- Knowledge of data governance, security and operational best practices for cloud platforms.
- Experience automating metadata collection, data movement and operational processes.
- Experience supporting cloud modernization and data migration initiatives.
- Knowledge of performance optimization and scalability considerations for cloud data platforms.
- Ability to troubleshoot complex technical problems and develop practical solutions.
- Strong analytical, organizational and communication skills.

Resource will support the following deliverables:

- Data pipelines and integration services
- Automated metadata collection and synchronization processes
- Cloud data platform implementation and configuration
- Data quality and lineage enablement
- CI/CD and DataOps automation
- Data migration and interoperability services
- Cloud-hosted data products and reusable data services
- Metadata and governance platform integrations

Desirable Skills (20%)

- Experience with Microsoft Fabric and Azure Data Services.
- Experience with Microsoft Purview.
- Experience with graph technologies and semantic repositories.
- Knowledge and understanding of AODA and related standards.
- Ability to meet tight deadlines and adapt to changing project priorities.

📌 DataOps/Cloud Data Engineer – Senior (Toronto)
🏢 InnosysTech
📍 Toronto