Top Data Jobs in Ottawa

Lead Andela Academy, scaling enterprise learning solutions in AI and Cloud. Build relationships, oversee team delivery, and drive revenue growth with high client satisfaction.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.

Configure and integrate Total Learning Architecture components (LMS, LOR, LRS, Synthetic Training Hub) to enable xAPI data pipelines, validate end-to-end data flows, implement learning analytics and Power BI reporting, support UAT, and provide SME guidance for cloud-native training content and simulation integrations.

As a Sr. Data Engineer, you'll design and manage data pipelines, enhance data quality, and leverage AI to streamline operations, driving the success of our AI growth platform for real estate.

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.

Collect and record pedestrian counts at designated intersections during AM and PM shifts in September/October 2026. Follow protocols, use a smartphone for data entry, work outdoors in varied weather, maintain safety and professionalism, and report to the Program Manager for School Zone Safety.

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.

Perform clinical review of oncology study participant-level data to ensure readiness for milestones (interim/final analysis, submissions). Conduct point-to-point and interpretive checks, generate and resolve queries, identify trends and safety signals, liaise with study team, and follow SOPs to maintain data quality and integrity.

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.

Senior-level role building and validating real‑world datasets and analyses. Responsibilities include programming (SAS/R/Python/SQL), cohort derivation, index date definition, applying GLM/logistic/Cox and propensity score methods, working with claims/EHR sources (Optum, HealthVerity, PharmMetrics), OMOP transformations, protocol/SAP review, QC/validation, documentation, and mentoring. AI/ML and LLM workflow usage is a plus.

Lead analytics and risk measurement at Shakepay: define risk metrics and decision frameworks, analyze fraud/scam patterns, build reporting, design data instrumentation and decisioning systems, evaluate controls with statistical and selective ML methods, conduct investigations, and communicate insights to influence engineering and product priorities.

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 implement risk measurement, decisioning, and detection systems. Analyze fraud, scam, and abuse patterns; build reporting and instrumentation; evaluate risk controls with statistics and selective ML; conduct deep-dive investigations; partner with engineering and cross-functional teams to improve data quality, decision frameworks, and operational tooling.

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 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.

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.

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.

Design, build, and optimize Databricks-based data and ML platforms. Own ETL pipelines, Delta Lake lakehouse, MLflow model lifecycle, MLOps, cluster optimization, RAG/LLM solutions, BI integration, and data governance with Unity Catalog.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Provide autonomous CRM operations and Power BI reporting support for a contracting executive: maintain Salesforce data hygiene, pull and QA reports, organize multi-state contracts, track key terms, produce market analysis and executive PowerPoint decks, document SOPs, and recommend process improvements.

Provide SKU-level demand forecasts, set reorder points and safety stock, reconcile inventory, analyze 3PL/carrier performance and shipping costs, build automated dashboards and SQL pipelines unifying Shopify, Amazon, and 3PL data, run ad-hoc promo and launch analyses, and partner with Growth and Operations to align stock and reduce logistics cost.