Top Data Jobs in Ottawa

Lead design and delivery of Azure-based data platforms and Data Lakehouse architectures. Architect Microsoft Fabric reporting, build scalable ETL/ELT pipelines, optimize SQL/Power BI semantic models, enforce data governance (PII, multi-tenant, retention), migrate legacy systems, mentor engineers, and create AI-ready pipelines feeding embeddings, vector stores, and feature stores.

Audit and monitor data labeling outputs, provide actionable feedback, support onboarding and training of annotators, enforce and improve guidelines, escalate workflow issues, and document findings to maintain high-quality human-in-the-loop AI data processes.

Evaluate AI model outputs, perform audit-based reviews, apply and improve guidelines, identify trends and failure modes, document findings, and collaborate with leads and cross-functional teams to refine quality standards.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

The Software Engineer will manage data collection for model training operations, enhance cloud infrastructure, and collaborate with AI scientists to improve data quality and scale.

Lead vision, roadmap, and hands-on delivery of a secure AI, GenAI, and data platform in AWS. Implement Amazon Bedrock and SageMaker powered GenAI and MLOps capabilities, establish secure data foundations, define guardrails/compliance automation, own platform reliability and onboarding, and drive cross-functional adoption and governance for regulated environments.

Design and operate distributed inference systems for LLMs, build large-scale data pipelines, and debug production issues while collaborating with researchers and ML engineers.

As a Senior Data Engineer, you'll build and manage scalable data platforms using AI tools to process high-volume data and support analytics. You'll own the data lifecycle, architect data models, and automate workflows, enhancing data accessibility for product and analytics teams.

The Product Data Analyst will analyze operational data, develop analytics frameworks, create dashboards in Tableau, ensure data integrity, and collaborate across teams to enhance decision-making and reporting.

Lead BI reporting and analysis for Advertising Technologies: design dashboards, define ETL/data models, create KPIs, resolve data quality issues, deliver recurring and ad-hoc reports, automate reporting workflows, document data logic, and collaborate with stakeholders to communicate insights.

Perform clinical review of oncology study participant-level data to ensure readiness for milestones (interim/final analyses, submissions). Conduct point-to-point and interpretive checks, generate and track queries, identify safety signals or protocol deviations, liaise with study teams, and follow SOPs to ensure data is clinically valid and submission-ready.

The Data Scientist will develop data labeling strategies, optimize datasets for LLMs, analyze data quality, and collaborate with engineering on data processing pipelines.

The Senior Data Scientist will lead data science strategy, develop models for lead qualification, fraud detection, and underwriting, and collaborate with product and engineering to enhance financial products.

The Data Engineering Lead oversees data engineering operations, manages teams, ensures data integrity, and drives innovation in data management and governance.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

Analyze large datasets to produce dashboards, metrics, and insights supporting product, care, and business decisions. Build BI infrastructure, run A/B and multivariate tests, perform ad-hoc analyses and visualizations, and collaborate with stakeholders and data scientists to inform strategy and operations.

Build and own a versioned, documented gold data layer from lakehouse silver tables for AI research. Transform, validate, and productize multi-modal datasets and pipelines (Databricks/PySpark) to support model development, evaluation, and production ML/LLM workflows while ensuring data quality, provenance, and regulatory controls.

Lead design, development, and implementation of data integration solutions for Oracle EPM Cloud (Planning, FCC, Reconciliation). Build ETL processes, configure DE/DM/OIC, perform data mapping/validation/testing, provide technical support and training, lead project teams, and recommend optimizations to ensure data accuracy and integration performance.

Design and architect large-scale distributed Big Data solutions using Java, Spark, and Hadoop/Cloudera. Lead global teams to build high-volume data processing and analytics pipelines, ensure robust testing (JUnit), and apply scripting for automation and data analysis.

Senior Java Big Data Developer with 8+ years building applications on Cloudera/Hadoop ecosystems using Spark and MapReduce. Responsible for designing performant Java (1.8+) solutions, data analysis of large datasets, unit testing (JUnit), and collaborating with/managing global technology teams. Preferred skills include Unix/Python scripting and familiarity with Hive, Impala, YARN, and Kafka.

Design, develop, test, and deploy high-performance Apache Spark/Scala data processing applications and ETL pipelines on Cloudera (CDH). Optimize Spark and platform performance, build data pipelines using HDFS, Hive, Impala, HBase, and Kafka, ensure data integrity and security, collaborate with data scientists and analysts, and implement version control and CI/CD for deployments.

Design, develop, and maintain data engineering solutions across the SDLC using Python (primary) and Scala (secondary). Build distributed data pipelines on Hadoop/Spark ecosystems, extend data processing platforms (Spark SQL, Hive, Starburst), manage CI/CD, and deploy on Kubernetes/OpenShift. Collaborate with stakeholders in Agile teams and ensure maintainable, reusable code.

Design and architect large-scale distributed big data solutions and ETL pipelines using Java, Scala, and Spark. Build and optimize Spark applications on Cloudera CDH (HDFS, Hive, Impala, HBase, Kafka). Ensure data integrity, troubleshoot performance issues, and implement version control and CI/CD for Spark workloads while collaborating with cross-functional teams.

Build and maintain responsive Angular UI components, collaborate with UX and backend teams, implement REST APIs and Python backend scripts, integrate basic ML models into data workflows, and participate in the full SDLC within Agile teams while ensuring code quality and performance.

Senior Data Engineer responsible for designing and validating data solutions, consolidating disparate data sources, documenting functional specifications, reviewing data models, supporting production deployments, investigating data quality issues, and collaborating with stakeholders and technology leads to ensure data completeness and lineage.