Top Data Jobs in Calgary

Design and deploy scalable data science and generative AI solutions: acquire and ETL data from S3/RedShift/Spark, analyze data quality, build/validate models (ML, NLP, networks), deploy models to production, and mentor teams while collaborating with stakeholders and engineering.

Design, develop, test, and support enterprise ETL/ELT data integration and pipeline solutions using Talend and relational databases. Build mappings, transformations, reconciliation, and reusable components; optimize SQL; administer Talend tooling; integrate REST APIs via Azure API Management; monitor and troubleshoot production pipelines; support data quality, governance, metadata, lineage, security, and SDLC processes while collaborating with stakeholders and using AI/automation tools for productivity.

Design, develop, deploy, monitor, and support Talend-based enterprise data integration solutions. Build ETL/ELT pipelines, SQL transformations, API integrations, and Talend administration (TMC, Remote Engine). Troubleshoot production data pipelines, perform data reconciliation, implement data governance and security controls, and collaborate with stakeholders to ensure compliant data movement across cloud and legacy systems.

Support the Financial Data product by translating roadmap goals into engineering requirements, creating mockups and business logic, querying PostgreSQL/Snowflake/Athena for data insights, performing data validation and QA, documenting product features, coordinating cross-team prioritization, and contributing to release communications.

Lead development of digital pathology AI models using whole-slide image data to predict clinical outcomes and morphologic features. Drive dataset selection and annotation, coordinate and mentor junior scientists, partner with bioinformatics, statistics, and clinical experts, produce analyses and visualizations for publication, and manage cross-team project execution to build diagnostic products.

Design, build, and operate a cloud-native data platform and ML infrastructure at scale. Own end-to-end pipelines from CDC to feature stores, model training/serving, monitoring, and data product SLAs. Apply distributed systems and MLOps practices, leverage LLMs/agentic systems, and translate technical issues to business impact.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Drive product and performance analytics for mobile app user acquisition: define core metrics, analyze campaign and product trends, build dashboards and data pipelines, support experiments and ML teams, automate reporting (including AI-powered workflows), and communicate findings and recommendations to stakeholders.

Lead subscription analytics: define KPIs, design experiments (A/B tests), analyze customer lifecycle, identify retention/growth opportunities, ensure data quality, and build dashboards to inform cross-functional decisions.

Perform high-level video captioning, action-based timeline segmentation, and visually-verifiable action labeling. Review and correct AI-generated captions, meet accuracy benchmarks, follow strict guidelines, and complete certification.

Lead high-impact analytical work partnering with senior executives to turn ambiguity into data-driven strategy. Design sophisticated analyses on large-scale data, mentor data science teams, build cross-functional trust, and deliver rigorous, decision-ready recommendations that influence long-term product and business strategy.

Ensure quality, consistency, and governance of enterprise master data through data analysis, reporting, and collaboration. Perform data mining, identify quality issues, develop dashboards, run system queries, maintain data, support supplier outreach, and meet SLAs while supporting business initiatives and process improvements.

Lead and scale end-to-end data annotation operations: set quality standards, build and manage an in-house annotation team and vendors, translate research into annotation guidelines, implement QA systems, drive AI-assisted labeling, partner with ML/CV and product, and own metrics and reporting.

Lead people analytics by building end-to-end models and production data pipelines, designing dimensional models, and creating LLM/NLP solutions. Translate statistical outputs into executive-ready insights, develop automated dbt/Snowflake workflows and dashboards, partner with HR systems owners and the enterprise data office, and enforce data governance and privacy for People data to support strategic workforce decisions.

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.

Lead full-cycle enterprise sales for data and intelligence consulting: originate pipeline, run discovery, manage complex multi-stakeholder deals, create SOWs with delivery teams, co-sell with partners, and meet revenue targets while leveraging AI tools.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

Abstract and enter clinical data from healthcare records, apply clinical operations policies, troubleshoot VPN/MFA access, maintain confidentiality, and provide guidance to less-experienced team members while ensuring data quality and workflow adherence.

Lead and build Burq's data and ML platform: own warehouse, ingestion, semantic layer, and BI; architect and ship forecasting, optimization, matching, and reliability models; implement feature pipelines, training/serving, and monitoring; drive AI agent initiatives; hire and grow a data/ML team; set governance, intake processes, and partner with product, engineering, and commercial stakeholders to align models with business impact.

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.

Perform product and player-behavior analysis for Marvel Strike Force using SQL/Python and reporting tools. Build recurring KPI reports, design/validate analytics tracking and experiments, partner with cross-functional teams, and use AI-enabled tools to accelerate workflows while ensuring data quality, privacy, and clear executive-ready insights.

Lead product execution for retail platforms, integrations, and data foundations. Establish data governance, define integration patterns and data contracts, improve fulfillment/OMS capabilities, evaluate vendors, and enable analytics and AI-driven automation to increase operational efficiency.

The Data Migration Specialist will manage end-to-end data migrations, ensuring data quality and effective communication with clients and internal teams while resolving challenges.