IT Data Solutions Developer

Dayforce; Toronto; On-site; CAD 90,000 - 120,000; Full time

Benefits offered by this job

Diversity programs

Paid time off

Well-being programs

Competitive compensation

Volunteer days

Career growth programs

Job summary

Ceridian is seeking a Data Engineer to design, build, and support modern data solutions across the organization. You will integrate, transform, and model data from multiple sources using Microsoft Fabric and Azure, creating governed, reusable data products for analytics and AI.

Collaborate with data engineers, analysts, architects, and business partners to deliver scalable, reliable data pipelines and advanced BI capabilities with Power BI and AI-enabled solutions.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Applied Math or related field.
• 2-5 years of professional data engineering experience.
• Strong SQL skills with data transformation and optimization.
• Experience with Python, PySpark, Spark SQL.
• Experience with Microsoft Fabric, Azure Data Factory, Synapse, Databricks.

Responsibilities

• Design, build, test, and support data pipelines ingesting and transforming data from multiple enterprise systems.
• Develop modern data solutions using Microsoft Fabric and Azure technologies (Fabric Lakehouse, OneLake, Data Factory/Pipelines).
• Transform data through raw, cleansed, curated, and consumption-ready layers using lakehouse patterns.
• Build and maintain reusable data models and trusted data products for analytics, self-service, and AI.
• Develop solutions using SQL, Python, PySpark, Spark SQL, and related data engineering tech.
• Monitor, troubleshoot, optimize, and improve reliability and performance of data pipelines.

Skills

SQL

Python

PySpark

Data Modeling

ETL/ELT

Azure

Fabric

Data Warehousing

CI/CD

Power BI

Education

Bachelor's Degree in CS/Engineering/Applied Math or related field

Tools

Azure Data Factory

Azure Synapse

Databricks

Fabric Lakehouse

OneLake

Git / Azure DevOps

Job description

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 modern 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.