Senior Data Integration Specialist

Company: CGIC
Department:
Business Intelligence

Employment Type:

Regular Full-Time
Work Model:
Hybrid (2 days in office)
Language:
English is required, French is an asset.

The Opportunity:

We are a leading Canadian financial services co-operative committed to being a catalyst for a sustainable and resilient society and our team is essential to deliver on this strategy. That’s why we prioritize our people, to ensure we provide a strong culture and development opportunities which enables our team to thrive and to live our purpose. The best part is that you will work with people that care passionately about you, our clients and our communities.
Our Business Intelligence team empowers decision making using leading edge science and analytics. We champion a scientific culture through our passion for continuous learning, diversity and innovation.

We strive to deliver a single version of truth, by providing our business partners with access to comprehensive data and valuable insights to help our organization achieve operational excellence.
As a Senior Data Integration Specialist, you will autonomously contribute to various initiatives by engineering data solutions for analytics purposes while also supporting the team through coaching. You will be responsible for providing business value through the creation; maintenance; implementation of back-end data solution (ie. Source System ingestion, ETL & Data Store) through the full software development lifecycle and effectively communicate said value to a business audience.
How you will create impact:
Proficiently working with data engineering tools: general purpose languages used in data engineering or generally in BI and related framework or interfaces, data querying and data handling and Dev Ops platforms.
Debug, analyze, and resolve complex database and SQL issues to ensure optimal performance and stability.
Investigate, troubleshoot, and perform root cause analysis on SQL performance issues and data discrepancies.
Autonomously contributes to assessing data quality and building automated controls.
Define and build data solutions (data models, data pipelines, APIs and more) and support others through execution.
Coach and mentor team members by sharing technical expertise, development best practices, and industry standards.
Proficiently develop analytic solutions to solve business problems by understanding the role of data in reporting, metrics, predictive models and other analytic solutions within the BI environment.
Contribute to the design of analytic solutions, considering scalability, automation, security, long term maintainability and performance.
Apply and promote software development lifecycle (SDLC) practices, including code reviews, testing, deployment standards, monitoring, and operational support.
Deeply understand the insurance domain (metrics, KPI, key insurance concept), business objectives, how your own tasks contribute to meeting the business objectives and how they are connected to enterprise goals.
Autonomously and efficiently communicate findings to a business audience.
To join our team:
You have 4-7 years of experience in the Data Engineering/Integration or other related field.
You have a Bachelor’s degree in, Computer Science or any other relevant field.
You have experience solving complex problems by taking a new perspective on existing solutions; and exercising judgment based on the analysis of multiple sources of information by providing clear recommendations for improvement.
You have strong knowledge and understanding of data analysis, programing, modeling techniques, data warehouse and data management, research, architecture and design.
You have strong knowledge of:
Data engineering and integration, Data modeling techniques, Data warehousing, Data management and governance, Software development lifecycle (SDLC) practices.
You have hands-on experience developing and supporting enterprise data solutions using modern cloud-based technologies such as: SQL, Python, Azure Synapse Analytics, Azure Data Lake Storage (ADLS), Git Hub and/or Azure Dev Ops.

Experience with the following technologies is considered an asset:
Databricks, Apache Spark / PySpark, Delta…