À propos de ce poste Senior Data Engineer (Contract) chez Concurrency
Who We Are
At Concurrency, we embody innovation. We're not just tech consultants; we are forward thinkers with a purpose. Our team thrives on disrupting the norm, constantly seeking the next challenge and pushing boundaries to redefine what's achievable. Recognized as a Microsoft Gold Partner and recipient of multiple Partner of the Year awards, Concurrency is synonymous with excellence. If you're fueled by the desire to transform technology into real-world solutions, join us and unleash your potential as a change catalyst.
Who We’re Looking For
We’re excited to add a Data Engineer to our Cloud, Data & AI Solutions Team. In this role, you’ll work with a team of customer-focused professionals who are committed to defining technical strategy, architecting, designing, and delivering end-to-end digital transformation. You'll demonstrate strong technical competence and business acumen through engaging in senior-level technology decision-making discussions related to agility, business value, data warehousing, and cloud-oriented data solutions.
At Concurrency, we believe in living out our core values every day. These principles guide our actions, decisions, and interactions:
Be Yourself: Be the best version of your whole self. Your authenticity matters.
Be Bold: Bravely and respectfully take risks and challenge the norm.
Have a Growth Mindset: Be open to learning and apply your expertise.
Be the Difference: Ensure that every interaction with your colleagues, clients and community improves their lives. Pay it forward.
Assume Positive Intent: Lead with giving the benefit of the doubt.
What You'll Do
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Design, build, and optimize scalable data solutions using Microsoft Fabric, Azure, and modern cloud data platform technologies.
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Partner with business and technical stakeholders to gather requirements and translate them into technical designs, data models, and implementation plans.
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Develop and maintain Fabric Data Factory pipelines, dataflows, notebooks, and orchestration processes for reliable data ingestion and transformation.
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Build and support Lakehouse architectures leveraging Bronze, Silver, and Gold (Medallion) layers to improve data quality, governance, and analytics readiness.
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Develop ELT/ETL solutions using SQL, PySpark, Python, and Fabric notebooks to transform and enrich enterprise data.
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Create and optimize data models that support reporting, self-service analytics, AI, and machine learning initiatives.
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Support migrations from legacy data platforms, on-premises databases, and third-party systems into Microsoft Fabric and Azure data services.
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Implement data quality, monitoring, security, and governance practices that align with enterprise standards.
What You'll Need
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Over 2 years of experience designing and delivering modern data solutions on Microsoft Azure and/or Microsoft Fabric.
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Experience developing and supporting Microsoft Fabric workloads including Data Factory, Lakehouse, Warehouse, Notebooks, or Real-Time Analytics.
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Understanding of Medallion Architecture (Bronze, Silver, Gold) and modern data engineering best practices.
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Experience building ELT/ETL pipelines using SQL, Python, PySpark, Data Factory, or similar cloud-native technologies.
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Strong SQL development skills, including stored procedures, data transformation logic, and performance optimization.
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Knowledge of dimensional modeling, star schemas, Data Vault, and other analytical data modeling techniques.
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Ability to gather business requirements and translate them into source-to-target mappings, data models, and technical solutions.
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Experience developing semantic models, reports, and dashboards using Power BI.
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Understanding of data governance, data quality, security, and performance considerations within cloud data platforms.
What Will Set You Apart
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Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or equivalent practical experience.
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Knowledge of OneLake, shortcuts, semantic models, and Fabric-native architecture patterns.
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Experience supporting AI, machine learning, or advanced analytics workloads.
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Familiarity with Azure Synapse Analytics, Azure Data Lake Storage, and related Azure data services.
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Experience with DevOps practices including Git, CI/CD pipelines, and infrastructure automation.
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Consulting or professional services experience with direct client engagement and solution delivery.
