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Senior Data engineer

@ Highspring

Toutes ses offres Site Web

Montréal, Québec

Temps plein5+ ans d’expérience
Postuler
SIGNAUX

Résumé des exigences :

  • Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related field.
  • 5+ years of experience in Data Engineering, Data Integration, or Cloud Data Platform development.
  • Strong hands-on experience building large-scale data platforms on Microsoft Azure.
  • Practical experience with Microsoft Fabric, including OneLake, Lakehouse, Data Factory, Spark, Notebooks, Data Warehouse, Real-Time Intelligence, Semantic Models, and Power BI integration.
  • Experience with Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL.
  • Experience with Git, Azure DevOps, automated testing, CI/CD, and release management practices.

Outils et compétences

Microsoft AzureMicrosoft Azure Data FactoryDatabricksPythonPySparkSQLData warehouseData modelsCI/CDDevOpsGitTroubleshootRoot cause analysisDocumentation
Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-11-08
Première détection par notre source
2026-11-10
Mise à jour du dossier source
2026-11-10

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Postuler
ChampValeur
Offres sur Jobsy4
Description

About Highspring

Highspring partners with organizations undergoing large-scale digital transformation initiatives, helping them modernize technology platforms and maximize the value of their data through innovative, business-driven solutions.

The Opportunity

We are seeking an experienced Data Engineer to design, build, and support scalable data solutions leveraging Microsoft Azure and Microsoft Fabric. In this role, you will work closely with architects, analysts, data scientists, and business stakeholders to deliver reliable data ingestion, integration, storage, transformation, and analytics capabilities in a high-volume environment.

What You'll Do

  • Design, develop, test, deploy, and maintain scalable batch and real-time data pipelines.
  • Build data ingestion and transformation workflows using Azure Data Factory, Microsoft Fabric Data Factory, Azure Databricks, Python, PySpark, and SQL.
  • Implement Lakehouse, Data Lake, and Data Warehouse solutions using OneLake, Azure Data Lake Storage, Fabric Lakehouse, Fabric Warehouse, and Azure Synapse Analytics.
  • Develop reusable data models, APIs, transformation frameworks, and integration components.
  • Optimize pipelines, Spark workloads, queries, storage formats, and compute resources for performance, reliability, and cost efficiency.
  • Implement data quality controls, monitoring, alerting, logging, lineage, and error-handling processes.
  • Support streaming and event-driven solutions using Event Hubs, Service Bus, Fabric Real-Time Intelligence, and related technologies.
  • Apply security, governance, privacy, access control, and data retention standards across the platform.
  • Build and maintain CI/CD pipelines using Azure DevOps and Git.
  • Collaborate with cross-functional teams to deliver production-ready data solutions.
  • Troubleshoot production issues, perform root-cause analysis, and drive continuous improvements.
  • Maintain technical documentation, data mappings, operational procedures, and solution diagrams.

What You'll Bring

  • Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related field.
  • 5+ years of experience in Data Engineering, Data Integration, or Cloud Data Platform development.
  • Strong hands-on experience building large-scale data platforms on Microsoft Azure.
  • Practical experience with Microsoft Fabric, including OneLake, Lakehouse, Data Factory, Spark, Notebooks, Data Warehouse, Real-Time Intelligence, Semantic Models, and Power BI integration.
  • Advanced proficiency in Python or PySpark and strong SQL skills.
  • Experience with Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL.
  • Strong understanding of ETL/ELT processes, dimensional modeling, data warehousing, Lakehouse architecture, Delta Lake, APIs, and batch/streaming data processing.
  • Experience with Git, Azure DevOps, automated testing, CI/CD, and release management practices.
  • Knowledge of data security, governance, lineage, observability, and monitoring concepts.
  • Excellent analytical, problem-solving, collaboration, and communication skills.

Additional Assets

  • Experience delivering cloud data platform modernization, migration, or transformation initiatives.
  • Knowledge of Medallion Architecture, Data Mesh, metadata-driven pipelines, and reusable engineering frameworks.
  • Experience with Infrastructure as Code using Terraform, Bicep, or ARM Templates.
  • Familiarity with containerization, orchestration, DevOps, and DataOps practices.
  • Experience working within regulated, enterprise-scale, or mission-critical environments.
  • Relevant certifications such as:
  • Microsoft Certified: Fabric Data Engineer Associate
  • Microsoft Certified: Azure Data Engineer Associate

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