At Ops Guru, we're a people-first, customer-obsessed company motivated by our passion for empowering organizations of all sizes to embrace the power of Cloud technology through impactful, reliable and scalable consultancy services.
Our team is made up of technical experts, creatives, salespeople, and many more. We work together to drive our mission forward and raise the bar for our customers daily, bringing their vision to life. We strive to be a workplace of inspired minds by fostering an environment that encourages cutting-edge thinking, where everyone can grow and contribute to achieving their goals.
Our long-term vision is to continue being an innovative and inspiring company that our customers and employees admire, and we invite you to join us
About the role:
Ops Guru's value to our customers centres around our ability to provide deep technical guidance based on their business needs. We achieve this by assigning small, virtual teams of highly skilled individuals to each client.
Within these teams, the Data Solutions Architect is responsible for providing technical expertise and leadership to Data Engineers, while also maintaining a systems view that is able to reconcile technical decisions with broader project goals.
Data Solutions Architects work alongside our Principal Consultants to ensure our project deliverables meet stakeholders' needs while upholding Ops Guru's quality and operational maturity standards.
What you'll be doing:
Project Delivery
Provide deep technical expertise and leadership across a range of cloud data technologies. You will be the go-to person for driving tool selection, resolving complex engineering issues, and guiding best practices during engagements.
Lead the design and implementation of data platforms to meet customers' business requirements.




Lead whiteboard design sessions with internal and external team members.
Identify and communicate technical risks as they emerge over the course of a project.
Work closely with Principal Consultants to extract project requirements during technical discovery sessions, define deliverables to meet those requirements, and break down those deliverables into a technical roadmap.
Lead teams of data engineers to execute project roadmaps. Provide guidance on technical tasks, priorities, and technical assistance when needed.
Manage scope within customer engagements. Identify changing requirements as they arise, determine their impact on scope, and ensure all stakeholders are aware and agree with the changes.
Maintain a close working relationship with the customer, as a "Trusted Advisor". Set clear expectations, challenge assumptions, solicit feedback, and take ownership of project deliverables.
Establishing credibility and building impactful relationships with our customers
Design and Delivery
Complex ETL/ELT processes, large-scale batch and real-time stream processing solutions, and optimizing data and schemas
Data Lakes using native cloud tools or leveraging 3rd party platforms (for example Snowflake or Databricks)
AI-based solutions for NLP, speech and video recognition, anomaly and fraud detection, chatbots, etc.
End-to-end data solutions from ingestion pipelines, cataloging, analysis,



and sharing insights (for example reports, dashboards, ML forecasts/predictions, etc.
Migrations and transformations of data services such as relational databases, No SQL databases, and Data Warehouses (heterogeneous and homogeneous)
Designing, building, training, and optimizing AI/ML solutions
Designing and integrating MLOps solutions to support model lifecycle automation
Other Technical:
Developing code using Python, Java, and Scala languages
Architect and operationalize solutions following best practices including data governance, privacy, lifecycle management, and cost optimization
Maintain relevant certifications on cloud and data technologies and stay informed of key industry trends
Leverage AI development tools (e.g., Cursor, Claude Code) to accelerate data architecture and pipeline delivery, applying architectural oversight to audit and refine AI-generated code for scalability, performance, and correctness.
Technical:
7+ years of experience in public cloud environments (AWS preferred).
5+ years of developing code using Python, Java, or Scala languages
Experience building complex data engineering pipelines and ETL/ELT tasks
Experience with relational databases (for example Oracle, SQL Server, My SQL, Postgres, Maria DB) or managed cloud RDBMS services (such as Amazon Aurora)
Experience with No SQL databases such as Mongo DB, Cassandra, Couch DB, Elastic Search, Neo4j, Dynamo DB, Big Table, etc.
Experience building batch processing and real-time processing systems.
Experience building Data Warehouses and Data Lakes
Experience with 3+ of the following:
Building real-time streaming solutions leveraging technologies such as: Kafka, Kinesis,

📌 Data Solutions Architect (Winnipeg)
🏢 OpsGuru
📍 Winnipeg