Sr Data Engineering Developer

Company: CGIC
Department:
Information Technology

Employment Type:

Regular Full-Time
Work Model:
Hybrid (2 days in office)
Language:
This role operates in English.
Additional Information:
This/these role(s) is/are currently vacant

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.

The Sr Data Engineering Developer is responsible for the design, development and optimization of data products and enterprise data solutions, ensuring the reliability and performance of data pipelines, APIs, and analytics solutions. This role requires a high level of autonomy in managing complex data pipelines, the ability to collaborate with key partners, and to support junior team members while delivering high-quality data for analysis and decision-making, automation, and insight generation.

• Working Autonomously, along with guiding junior colleagues to:
  • Execute data extraction, cleansing, reconciliation and assess its characteristics, such as data quality.
  • Design and maintain a physical and logical data model.
  • Use data engineering tools for data querying (ex: SQL), data handling (ex: py Spark, stored procedures), data storage (ex: ADLS), cloud-based development, using tools such as Python, Databricks and data lake platforms.
  • Contribute to building scalable data solutions (data pipelines, APIs and more), reusable frameworks, and AI-enabled capabilities that support automation and advanced analytics.
  • Bring data to visualization tools by implementing the semantic layer.
• Applying proactive performance optimizations and monitoring of data solutions, such as alerts, while improving scalability, maintainability, and overall architecture.
• Performing research and analysis to solve real-world business problems.
• Working Autonomously, along with guiding junior colleagues to:
  • Use Dev Ops platforms (ex: Git Hub) and manage infrastructure deployments through code (ex: Terraform).
  • Configure and use continuous integration and deployment (CI/CD) pipelines, and our infrastructure (ex: Databricks environments) to properly develop and deploy data solutions.
  • Promote and comply with security requirements on the platforms and environments used by our data solutions.
• Delivering production ready code (ex: no technical debt, using proper frameworks) and reusable approaches that reduce technical debt.
• Identifying opportunities to collaborate, innovate, and make data-driven decisions, with the ultimate goal of bringing value to the business.
• Partnering with business and technology stakeholders to drive business value.

• You influence change and are committed to continuous improvement, in order to exceed client expectations.
• You leverage critical thinking skills to identify problems and proactively propose solutions.
• Your strong communication skills allow you to clearly convey messages.
• You’re an effective team player who shares knowledge to support our peers

• You have a degree in Computer Science, Information Systems, or related field is required. An advanced degree is an asset.
• You have 3-5 years of experience in Data-adjacent role.
• You have 3+ years of experience in data engineering with experience in building modern data platforms and data products, along with designing, developing and supporting data or software solutions.
• You have 3+ years of experience implementing data solutions (Azure preferred).
• You have advanced knowledge of data modeling, ETL processes, data warehousing concepts, and best practices in data engineering and analytics.
• You have hands-on experience with the following technologies and concepts:
  Python, Azure Data Lake Storage (ADLS) or equivalent data lake platforms, Azure Synapse SQL, Purview, OpenAI API Standard, Pandas/ Polars, REST APIs, Object Oriented Programming…