About the opportunity
The Enterprise Data Team is looking for a Data Engineer to design, build, and support modern enterprise data solutions that enable analytics, business intelligence, and emerging AI capabilities across the organization.

In this role, you will integrate, transform, model, and engineer data from a variety of sources using Microsoft’s modern cloud data platform, including Microsoft Fabric and Azure. You will help create trusted, governed, reusable data products that make enterprise data easier to discover, analyze, and use across reporting, self-service analytics, and AI-enabled solutions.

You will work closely with data engineers, architects, analysts, business partners, and other technology teams to deliver scalable and reliable data solutions while continuing to grow your expertise in cloud data engineering and emerging AI technologies.

What you’ll get to do

Design, build, test, and support data pipelines that ingest and transform structured and semi-structured data from multiple enterprise systems.
Develop contemporary data solutions using Microsoft Fabric and Azure technologies, including Fabric Lakehouse, OneLake, Data Factory/Pipelines, notebooks, Spark, and SQL-based workloads.
Transform data through raw, cleansed, curated, and consumption-ready layers using modern lakehouse and medallion architecture patterns.
Build and maintain reusable data models and trusted data products that support analytics, Power BI, self-service, and emerging AI use cases.
Develop solutions using SQL, Python, PySpark, Spark SQL, and related data engineering technologies.
Monitor, troubleshoot, optimize, and improve the reliability and performance of data pipelines, transformations, and data products.
Implement data quality, security, privacy, governance, and access-control practices that improve trust in enterprise data.
Explore and prototype new capabilities across Microsoft Fabric, Azure, analytics,



and AI technologies through proofs of concept.
Participate in source control, automated deployment, CI/CD, code reviews, testing, and other modern engineering practices.
Collaborate with data architects, analysts, governance teams, application teams, and business stakeholders to deliver enterprise data solutions.

What’s in it for you
Encouragement to be the best version of yourself at and away from work:

YOUnity diversity and inclusion programs
Amazing time away from work programs

Support for your total well-being through our Live Well, Work Well programs targeting all aspects of your life
Recognition for your contributions through excellent pay, perks, and rewards
Giving where you’re living: volunteer days, Ceridian sponsored events, and our very own charity, Ceridian Cares
Opportunities to fuel your career growth through numerous internal and external programs and events

Skills and experience we value

A Bachelor’s Degree in Computer Science, Engineering, Applied Math or Business or equivalent degree and experience
2–5 years of professional experience in data engineering, data development, analytics engineering, or a related field
Strong SQL skills, including experience with data transformation, query optimization, and relational data concepts.
Experience with Python, PySpark, Spark SQL, or similar data engineering languages and frameworks.
Experience building ETL/ELT pipelines using Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks or comparable technologies.
Experience with data modeling, dimensional modeling,



data warehousing, lakehouse architectures, or business intelligence solutions.
Familiarity with cloud data storage, data lakes, and modern file/table formats such as Parquet and Delta.
Experience with source control and CI/CD practices using Git, Azure DevOps, GitHub, or similar technologies.
Experience with Power BI or another modern business intelligence and visualization platform.
Understanding of data security, data quality, governance, and responsible handling of enterprise data.
Strong problem-solving skills and the ability to troubleshoot technical issues, research alternatives, and recommend solutions.
Demonstrated ability and enthusiasm for learning new cloud, data, and AI technologies.

What would make you really stand out

Hands-on experience with Microsoft Fabric, including OneLake, Lakehouse, Fabric Data Factory/Pipelines, notebooks, Spark, Warehouse, or semantic models.
Experience implementing medallion/lakehouse architectures using Delta Lake or similar technologies.
Experience with Microsoft Azure data services such as Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, or Azure Databricks.
Exposure to Generative AI or AI-enabled data solutions using technologies such as Azure AI Foundry, Azure OpenAI, Microsoft Copilot, or comparable platforms.
Understanding of AI data patterns such as embeddings, vector search, retrieval-augmented generation (RAG), or preparing enterprise data for LLM-based applications.
Experience using AI-assisted development tools to improve engineering productivity while following appropriate security, governance, and code-quality practices.
Experience developing reusable data products or APIs/services that make governed enterprise data available to analytics and AI applications.
Relevant Microsoft Azure, Fabric, Power BI, or data engineering certifications.

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