Data Engineering Solutions Architect

About the role

You will own the end-to-end design of modern data solutions that fuse robust data engineering practices with enterprise-grade data architecture. You will act as the technical visionary for client engagements, defining target states and guiding implementation details from discovery through deployment. You will translate ambiguous business problems into scalable, reliable data architectures that drive real business outcomes. You will mentor junior team members by providing hands-on technical leadership and clear communication of complex concepts. You will challenge the status quo by introducing innovative patterns that improve performance, governance, and time-to-value. You will serve as the trusted advisor who balances strategic vision with pragmatic delivery constraints. You will continuously evaluate emerging technologies and determine where they create tangible client value.

Key facts

What you'll do

Analyze client business requirements and translate them into scalable, secure, and cost-effective data architecture roadmaps.

Design logical and physical data models using industry-standard tools such as Erwin, ensuring alignment with normalization principles, naming conventions, metadata standards, and data governance.

Reverse engineer existing legacy databases and diverse source schemas into clear, traceable Entity Relationship Diagrams (ERDs) that serve as blueprints for migration or modernization.

Own the schema lifecycle and change control process, including versioning, impact assessment, and controlled deployment across development, test, and production environments.

Architect end-to-end data pipelines using a mix of low-code/no-code and code-first tools, including SSIS, Azure Data Factory, Alteryx, and Power Automate, to meet varied integration needs.

Develop and optimize robust data ingestion, transformation, and integration workflows that connect to a wide range of structured and unstructured data sources.

Implement and enforce ETL/ELT best practices to guarantee data reliability, accuracy, scalability, and performance under production loads.

Design and build analytics-ready data warehouses and data marts, creating reusable data assets that empower reporting, advanced analytics, and executive dashboards.

Troubleshoot intricate pipeline, performance, and data quality issues using a solution-focused, investigative approach that minimizes client downtime.

Collaborate with data scientists and business stakeholders to ensure database platform designs support SQL Server, Databricks, MySQL, PostgreSQL, and other cloud and on-premise data platforms.

Lead requirement gathering sessions with clients, actively listening to uncover data-related challenges and uncover opportunities for strategic data leverage.

Translate highly technical concepts into clear, actionable recommendations that resonate with both technical and non-technical executive audiences.

Contribute to comprehensive solution designs, architecture documentation, project plans, and technical deliverables that keep engagements on schedule.

Work seamlessly within cross-functional project teams to ensure proposed solutions align with client objectives, regulatory requirements, and operational realities.

Support the delivery of high-quality consulting engagements where clarity, outcomes, and measurable value are the ultimate measures of success.

Requirements

Bring 5-7 years of hands-on experience in data engineering, data architecture, or combined roles that span both technical design and implementation.

Demonstrate strong, practical experience with data modeling tools such as Erwin (or equivalent) and a deep understanding of logical and physical modeling techniques.

Show a proven track record of designing and managing schema lifecycle and change control, including versioning, impact analysis, and deployment strategies.

Exhibit solid architectural judgment around SQL Server, Databricks, MySQL, PostgreSQL, and additional cloud or on-premise data platforms.

Have experience designing and building data pipelines using SSIS, Azure Data Factory, Alteryx, Power Automate, and related integration technologies.

Possess strong attention to detail, ensuring that naming conventions, metadata management, and data governance are embedded in every design.

Communicate effectively and professionally while wearing multiple hats, navigating shifting priorities, and maintaining quality under tight timelines.

Nice to have

Experience with additional database platforms or data tools not explicitly listed that are common in enterprise environments.

Background in regulated industries where data governance, auditability, and compliance add complexity to data initiatives.

Practical notes

This is a full-time position based in Toronto.

The role may involve travel to client sites as required.

Candidates must be authorized to work in Canada without sponsorship at the time of application.