Data Product Analyst

Compunnel, Inc.; Edmonton; On-site; CAD 110,000 - 150,000; Full time

Job summary

Compunnel, Inc. is seeking an experienced Data Product Analyst to design, develop, and operate analytics-ready data products on Microsoft Azure.

The role focuses on building scalable data pipelines and curated datasets using Azure Data Factory, Databricks, Synapse Analytics, Delta Lake, Python, and SQL to support reporting, self-service analytics, data science, and business decision-making. The candidate will collaborate with product owners and cross-functional teams to ensure data products are

Qualifications

• 9+ years of relevant experience in data analytics or data engineering.
• Experience designing data solutions for trusted, analytics-ready datasets using tools like Azure, Python, SQL.
• Strong knowledge of data governance, security, and data quality practices.
• Experience with self-service analytics and data products.

Responsibilities

• Collaborate with stakeholders and cross-functional teams to define data product objectives, success criteria, and requirements.
• Design and implement secure, scalable data pipelines and data products on Microsoft Azure (Data Factory, Databricks, Synapse, Delta Lake).
• Develop ingestion, transformation, and orchestration pipelines using Python, PySpark, SQL, and Delta Lake.
• Build and manage Databricks workflows, jobs, notebooks, and clusters for high-volume data operations.
• Create analytics-ready datasets, data marts, and semantic layers for reporting and data science.
• Implement data quality, security, governance, monitoring, and operational support for data products.

Job description

Job Summary

The Data Product Analyst designs, develops, and operates trusted, analytics-ready data products on Microsoft Azure. This role builds scalable data pipelines and curated datasets using Azure Data Factory, Databricks, Synapse Analytics, Delta Lake, Python, and SQL to support reporting, self-service analytics, data science, and business decision-making. The position collaborates with product owners and cross-functional teams to ensure that data products are secure, governed, reliable, and aligned with organizational objectives.

Key Responsibilities

• Collaborate with business stakeholders, product owners, architects, and delivery teams to define data product objectives, requirements, success criteria, and implementation priorities.
• Design and implement secure, scalable data solutions using Azure Storage, Azure SQL, Azure Synapse Analytics, networking services, service principals, and managed identities.
• Develop and optimize enterprise-grade ingestion, transformation, and orchestration pipelines using Azure Data Factory, Azure Databricks, Python, PySpark, SQL, and Delta Lake.
• Build and manage Databricks Workflows, Jobs, Notebooks, clusters, and related processing environments to support reliable and high-volume data operations.
• Design analytics-ready datasets, data marts, semantic layers, and data products for self-service reporting, data science, machine learning, and operational analytics.
• Implement data quality, security, governance, monitoring, error handling, performance optimization, and operational support processes for data products and pipelines.
• Use AI and automation tools to improve code generation, data analysis, testing, documentation, monitoring, and productivity throughout the data engineering lifecycle.

Required Qualifications

• Minimum 9 years of relevant experience.
• Minimum 3 years of experience designing data solutions for trusted, analytics-ready datasets using tools such as Power BI and Synapse, including semantic layers, data marts, and data products.
• Minimum 4 years of experience using Git or GitHub for version control, collaborative development, code management, code review, and integration with data engineering workflows.
• Minimum 3 years of experience using Azure services such as Storage, SQL, Synapse, and networking to implement scalable and secure data solutions.
• Demonstrated experience implementing secure authentication for data pipelines and integrations using service principals and managed identities.
• Minimum 5 years of experience using Python, including PySpark, and SQL to develop, orchestrate, optimize, and troubleshoot enterprise-grade ETL/ELT workflows.
• Minimum 3 years of hands-on experience with Azure Databricks, Delta Lake, Workflows, Jobs, Notebooks, and cluster management.
• Minimum 1 year of experience using AI for code generation, data analysis, automation, productivity improvement, and data engineering workflow support.

Preferred Qualifications

• Minimum 6 years of experience performing business requirements analysis related to data manipulation, transformation, cleansing, and data wrangling.
• Minimum 6 years of experience with Microsoft SQL Server, including database design, optimization, and administration in enterprise environments.
• Experience with Microsoft Fabric and Azure Synapse Analytics, RESTful API integration, message queueing technologies such as ActiveMQ or Azure Service Bus, and cross-functional delivery of software applications and data products.