Top Data Engineer Jobs in Calgary

The Data Engineer will assist clients with SAP security design, implement SAP security, develop authorization profiles, and conduct security reviews.

Build, maintain, and troubleshoot ELT/data pipelines from multiple structured and unstructured sources. Support analysts by developing requirements and solutions, implement web-scraping for public data, and monitor production ELT processes and incident response.

Design, build, and maintain ETL/ELT pipelines and the Bronze/Silver layers of a Databricks Delta Lake lakehouse. Ingest batch and near-real-time data, implement data-quality checks, monitoring, lineage, governance, and secure access. Troubleshoot pipeline failures, design scalable schemas, and document architecture, integrations, and dependencies.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Design, build, and scale Snowflake ingestion pipelines and ML/LLM systems. Create agentic tooling to generate, test, and maintain pipelines. Collaborate with analysts, data scientists, and product teams to deliver reliable, high-performance data infrastructure and operationalize models for an AI-first e-commerce platform.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

Lead end-to-end data and ML pipelines for onboarding and fraud decisions: ingest streaming and batch sources, build feature platform and entity resolution, productionize ML models, enforce PII/data governance, and set technical direction while mentoring engineers and ensuring low-latency, reliable serving.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

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, 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.

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, 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.

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, build, and maintain scalable data systems and ETLs on GCP; connect production data to business systems; generate analytics and ML-driven insights for GTM teams; work cross-functionally and introduce modern tools (Airflow, DBT, Presto, Hightouch).

Lead design and implementation of scalable, secure Forma Data cloud services. Act as technical lead across full software lifecycle, write and operate cloud services, mentor engineers, solve complex distributed-system problems, and collaborate globally to integrate SaaS products with Autodesk tools.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

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.

Design and implement real-time MAC data-plane software for high-throughput satellite links. Build packet-processing pipelines, queue and buffer management, retransmission and loss recovery, and integrate with PHY, modem, FPGA, DMA, and SoC hardware. Optimize for low latency and high throughput using zero-copy, scatter-gather, lock-free structures, and hardware offload. Lead architecture through prototyping, hardware integration, performance qualification, and operational deployment while diagnosing timing and synchronization issues.

Design and implement automated data quality frameworks and tests for BigQuery-based pipelines. Collaborate with data engineers and product to define data contracts and quality gates, build observability and anomaly detection, validate complex ELT/ETL processes, and integrate data tests into CI/CD workflows. Drive improvements in documentation, governance, and pipeline reliability.

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.