RQ11576 – Data Ops/Cloud Data Engineer – Senior

Job summary

Design, develop, optimize, and operate cloud data pipelines, integration services, and data platforms, including automated metadata, data quality, lineage, and governance capabilities. Support cloud data migration, interoperability, CI/CD and DataOps automation, and the delivery of reusable cloud-hosted data products and services.

Job details

Client: Ministry of Public and Business Service Delivery and Procurement – RQ11576 We are seeking a Senior Data Ops/Cloud Data Engineer with extensive experience in cloud-based data platforms, data engineering, data pipeline development, integration services, and DataOps practices. The ideal candidate will have hands-on experience with Databricks, Delta Lake, Databricks SQL, Medallion Architecture, Azure Data Services, Azure Data Factory, and Informatica or equivalent integration platforms. The successful candidate will support the design, development, optimization, automation, and operational management of cloud data solutions, including metadata management, data governance, data quality, data migration, and enterprise data interoperability. Role Snapshot Job Title: RQ11576 – Data Ops/Cloud Data Engineer – Senior Client: Ministry of Public and Business Service Delivery and Procurement Work Location: 595 Bay Street, Toronto, Ontario, Canada Work Arrangement: Onsite – 5 Days per Week Estimated Start Date: September 21, 2026 Estimated End Date: October 1, 2027 Business Days: 283.00 Extension: Probable after the initial mandate Hours: 7.25 hours per day Security Level: No Clearance Required Must Have Experience with Databricks, Delta Lake, and Databricks SQL. Knowledge of Medallion Architecture. Experience with Azure Data Services and Azure Data Factory. Experience with Informatica or equivalent integration platforms. Experience operationalizing common data models and metadata repositories. Nice to Have Prior Ontario Public Service (OPS) or public sector experience. Experience with Microsoft Purview and Microsoft Fabric. Description Responsibilities Design and develop data pipelines from source systems to end users. Optimize data pipelines to improve performance, efficiency, and reliability. General Skills Experience with cloud data platforms, data management, and data exchange tools and technologies. Experience with commercial and open-source data and database development and management, specializing in data storage and the configuration and management of Cloud Data as a Service (DaaS), application Database as a Service (DBaaS), Data Warehouses as a Service (DaaS), and other storage platforms in both cloud and on-premises environments. Experience with data pipeline and workflow development, orchestration, deployment, and automation, specializing in programming and pipelines to create and manage data flows and data movement. Experience with cloud data engineering, including familiarity with different programming languages and the ability to integrate multiple platforms to create data pipelines, automate tasks, and write scripts. Experience with DataOps principles, best practices, implementation, and Agile project development and deployment. Experience with Continuous Integration/Continuous Development/Deployment (CI/CD) and data provisioning automation. Experience with digital products, data analysis, data exchange, data provisioning, and data security. Extensive expert experience in designing, developing, and implementing data conversion and migration of Very Large Data (VLD) across Online Analytical Processing (OLAP) and Online Transaction Processing (OLTP) environments to Cloud Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS) environments. Experience in the design, development, and implementation of fact/dimension models, data mapping, data warehouses, data lakes, and data lakehouses for enterprise environments. Experience managing cloud data services for project delivery, including storage, repositories, data lakes, data lakehouses, key vaults, virtual machines, disks, and related services. Experience with structured, semi-structured, and unstructured data collection, ingestion, provisioning, and exchange, including the technological development and operational support of enterprise data warehouses, data lakes, and data lakehouses. Experience with DataOps performance monitoring and tuning. Excellent analytical, problem-solving, and decision-making skills, along with strong verbal and written communication, presentation, interpersonal, and negotiation skills. A team player with a proven track record of meeting deadlines. Experience And 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 modern 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. Experience collaborating with architects, data modellers, and governance teams to operationalize data standards, metadata, and common data models. 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 Deliverables The 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 the Accessibility for Ontarians with Disabilities Act (AODA) and related standards. Ability to meet tight deadlines and adapt to changing project priorities. How to Apply If you are interested and your profile matches the requirements, kindly send the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, October 26, 2026, at 10:00 AM EST. Mandatory Documents Updated Resume in Word format (Mandatory) References (Mandatory) Expected Hourly Rate (Mandatory) Visa Status (Mandatory) LinkedIn ID (Mandatory) Without the mandatory documents, we cannot submit a candidate. WhatsApp Group For daily job updates, you can also join our WhatsApp group using the link below: Join our WhatsApp Group Note Onsite 5 days per week. Email is the best way to reach us. You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.

What you’ll do

Design, develop, optimize, and operate cloud data pipelines, integration services, and data platforms, including automated metadata, data quality, lineage, and governance capabilities. Support cloud data migration, interoperability, CI/CD and DataOps automation, and the delivery of reusable cloud-hosted data products and services.

Requirements

Requires extensive senior-level experience with cloud data engineering, Databricks, Delta Lake, Databricks SQL, Medallion Architecture, Azure Data Services, Azure Data Factory, and Informatica or an equivalent integration platform. Candidates should also have expertise in DataOps, scalable pipelines, metadata and governance, data migration, cloud platform operations, and collaboration with architecture, modelling, and governance teams.

Listed skills

• CI/CD · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Databricks
• Delta Lake
• Databricks SQL
• Medallion Architecture
• Azure Data Services
• Azure Data Factory
• Informatica
• DataOps
• Data Pipeline Development
• ETL/ELT
• Metadata Management
• Data Governance
• Data Quality
• Data Migration
• CI/CD
• Microsoft Purview

Job areas

• Technology
• Data & Analytics
• Software
• Government & Public Sector

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