Top Data Engineer Jobs in Ottawa

Perform L3 network troubleshooting and RCA on production enterprise networks, review telemetry/logs/configs, label and annotate network behaviors for ML training, and help define schemas and data pipelines to support AI-driven infrastructure.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

Lead the design and development of a data platform, integrating data sources, driving architecture migration, and ensuring robust data governance and API development.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and data models optimized for AI/ML. Manage orchestration, data quality, governance, and CI/CD (ADO → GitHub) while collaborating with cross-functional teams in Agile delivery.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Lead optimization and scaling of Snowflake architecture, build resilient ELT/ETL and MLOps pipelines, implement data observability, automate workflows with AI-assisted tools, and design enterprise semantic models to support analytics and commercial data products.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

Own and operate the data plane: develop Envoy/WASM filters for deep packet inspection, deploy and manage EKS workloads with Helm/GitOps and CI/CD, integrate Redis sidecars, provide observability (Prometheus/Grafana/OpenTelemetry), ensure reliable audit log streaming, and author ADRs as the data plane evolves.

Design and implement automated validation and testing frameworks for data connectors; modernize connector platforms; investigate and resolve authentication, connectivity, and performance issues; build diagnostics, telemetry, and CI/CD to improve reliability and quality across cloud and on-premises data sources; mentor and contribute to engineering best practices.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Design, build, and maintain robust terabyte-scale data pipelines and stream-processing applications. Collaborate with product teams, participate in full SDLC, automate tests and deployments, monitor operations, and contribute to technical strategy and continuous improvement. Participate in on-call rotation.

Design and build operational data systems, including pipelines, storage layers, and APIs for near real-time enforcement and insights, balancing streaming and batch paradigms.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Senior Data Engineer will lead the design and development of scalable data infrastructure for analytics and AI capabilities, ensuring compliant data processing systems and improving the data platform.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, collaborate with teams, and uphold data governance at Mozilla.

The Senior Data Platform Engineer will design and operate a unified data platform, ensuring reliable data flows and collaborating across teams to shape data strategy and architecture.

Own technical execution of customer data migrations: explore source systems, export data, author declarative version-controlled mappings, transform and validate data, run end-to-end migrations on internal platform, build reusable templates/validation, troubleshoot discrepancies, and document mapping and transformation logic for auditable production cutovers.

Own and evolve ClickHouse's Python connectors and SDKs; build integrations with orchestration and transformation tools; design AI/LLM connector patterns for RAG, vector search, and feature pipelines; engage with open-source community; collaborate across product and engineering to prioritize and ship production-grade data integrations.

Lead design and implement a scalable Medallion lakehouse on GCS and Databricks. Build and govern ingestion and transformation pipelines (Astro/Airflow, PySpark, Delta Live Tables), apply domain-driven data modeling, manage Unity Catalog access and lineage, collaborate with analytics and vendors, and proactively surface risks with clear documentation.