Specialist Data & Analytics

Chartwell Retirement Residences

$75K — $95K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Undergraduate degree in Computer Science, Engineering, Mathematics, or related STEM field; Master’s degree preferred.
  • Snowflake certification (e.g., SnowPro Core or Advanced Architect) strongly preferred.
  • 3-5 years of hands-on experience with a modern data stack, specifically in Snowflake, Azure, SQL, and Python.
  • Functional experience with data visualization tools, particularly Power BI, is required.
  • Experience with DevOps practices is a strong asset.

Responsibilities

  • Develop, optimize, and maintain data pipelines and ETL processes using Azure Data Factory and Snowflake.
  • Write complex SQL queries and Snowflake stored procedures for data transformation and reporting.
  • Create and deploy scalable Python scripts and Azure Functions for automation and advanced analytics.
  • Collaborate with business stakeholders to understand and document data requirements.
  • Support data governance and quality assurance practices across the organization.
  • Design and document enterprise data models and pipelines.
  • Develop and maintain analytical reports and dashboards using Power BI.

Benefits

  • Flexible hybrid work model with the possibility of remote work.
  • Opportunities for professional development and certification in advanced analytics tools.
  • Dynamic work environment with collaborative cross-functional teams.
  • Engagement in cutting-edge projects that enhance data management capabilities.
Full Job Description
Job Description

The Opportunity
We are seeking a highly skilled and motivated Data and Analytics Specialist to join our growing Data and Analytics team. The ideal candidate will bring deep technical expertise in Snowflake, Azure cloud services, SQL, Python and Power BI, to help design, develop, and optimize data solutions that support strategic initiatives across the organization.
Key Accountabilities
  • Develop, optimize, and maintain robust data pipelines and ETL processes using Azure Data Factory, Azure Data Lake, and Snowflake.
  • Write, read, and debug complex SQL queries and Snowflake stored procedures to support data transformation and reporting needs.
  • Create and deploy scalable Python scripts and Azure Functions for automation, data processing, and advanced analytics.
  • Collaborate with business stakeholders to understand data requirements and translate them into technical specifications.
  • Support data governance, quality assurance, and metadata management practices across the organization.
  • Contribute to the design and documentation of enterprise data models and pipelines.
  • Develop and maintain analytical reports, dashboards and semantic models using Power BI
  • Monitor pipeline performance and implement improvements for reliability, scalability, and efficiency.
  • Stay current with industry trends and best practices in cloud data engineering and analytics.
Qualifications
Education:
  • Undergraduate degree in Computer Science, Engineering, Mathematics, or related STEM field; a Master's degree is an asset.

Experience:
  • Snowflake certification (e.g., SnowPro Core or Advanced Architect) strongly preferred.
  • At least 3-5 years of experience using a modern data stack with hands-on use of:
    • Snowflake (warehousing, streams, tasks, UDFs)
    • Azure Data Factory, Azure Data Lake, Azure Functions
    • SQL (advanced query development and debugging)
    • Python (data processing and automation)

Skills & Abilities:
  • Functional experience with data visualization tools (e.g., Power BI) is required.
  • DevOps practices is a strong asset.
  • Strong analytical, communication, and problem-solving skills.
  • Demonstrated ability to work independently and collaboratively in a fast-paced environment.

Effort
  • Requires sustained mental focus for data analysis, debugging, pipeline optimization, and report development
  • Involves frequent use of computer systems and cloud-based tools for extended periods
  • Requires multitasking and prioritizing requests from multiple stakeholders in a dynamic environment
  • Attention to detail is critical when handling complex data queries, coding scripts, and quality checks

Working Conditions
  • Work is primarily performed in a corporate office setting with the flexibility of a hybrid work model
  • May involve occasional extended hours during system deployments, data migrations, or project deadlines
  • Requires regular virtual collaboration with cross-functional teams and business stakeholders
  • Must be comfortable working in a fast-paced, agile, and evolving technical environment


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