Data Engineer

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At CI, we see a great place to work as one that is a safe place for everyone to have a voice, where people are empowered to take ownership over meaningful work, where there is an opportunity to grow through stretching themselves, where they can work on innovative products and projects, and where employees are supported and engaged in doing so.

We are currently seeking a Data Engineer to join the Data and Analytics team in the Wealth Technology group at CI Wealth. The Data and Analytics team supports the organization through data management, data governance, reporting, and business intelligence and insights. The successful candidate will work on data pipeline and data transformation tasks that underly these strategic pillars. The ideal candidate will have a strong background in data pipeline implementation in a cloud environment.

WHAT YOU WILL DO

• Collaborate with business teams and Data Analysts to gather and understand requirements, ensuring alignment with business objectives and data needs.
• Translate business needs into detailed technical requirements in collaboration with subject matter experts (SMEs) to ensure accuracy and feasibility.
• Recommend and design scalable, efficient, and effective data architectures and workflows to support current and future business requirements.
• Design, develop, and maintain data assets to enable seamless extraction, transformation, and loading (ETL/ELT) processes from diverse data sources, making data accessible to client-facing applications, data warehouses, and internal tools.
• Build, operate, and optimize highly scalable and reliable data pipelines and infrastructure to support analytics, reporting and operational use cases.
• Drive end-to-end ownership of projects, including planning, development, testing, and deployment, ensuring timely and successful delivery.
• Collaborate with Quality Assurance (QA) and Support teams to identify, troubleshoot, and resolve issues in production environments, ensuring the stability and reliability of data systems.
• Work with Release Management to plan, coordinate, and implement data pipeline updates, adhering to deployment standards and minimizing disruption to production systems.
• Implement and enforce best practices for observability, data lineage, and governance, ensuring transparency, reliability, and compliance across all data systems.
• Support and mentor junior team members, fostering a collaborative and growth‑oriented environment while providing technical guidance and expertise.
• Lead or participate in data migration projects, transitioning legacy systems to modern platforms and architectures while minimizing disruption and data loss.

WHAT YOU WILL BRING

Experience

• Minimum of 3 years of professional experience in data engineering, with a strong focus on designing, developing, and optimizing scalable data pipelines, ETL/ELT workflows, and data integration solutions using modern cloud technologies.

Education/Training

• Post‑secondary degree in a quantitative or technical discipline (e.g., Computer Science, Engineering, Mathematics, or related field).

Knowledge, Skills, and Abilities

• Comprehensive understanding of data pipeline and modern data stack architectures, with hands‑on experience in cloud‑based platforms such as AWS, Azure, or GCP, and data platforms such as Snowflake, Databricks, or Redshift.
• In‑depth knowledge and practical experience with the following tools and concepts:
• Data storage repositories: SFTP, AWS S3
• Job scheduling and orchestration:
  Apache Airflow, AWS Step Functions
• ETL/ELT tools and workflows:
  Snowflake, PySpark, AWS Glue, AWS Lambda, Slowly Changing Dimensions (SCD)
• CI/CD and infrastructure automation:
  Bitbucket, Git, Jenkins, Cloud Formation, Terraform, Flyway
• Strong understanding of observability, data quality, and data lineage implementation to ensure transparency and monitoring of data pipelines.
• Excellent analytical, problem‑solving, and communication skills (both written and verbal).
• Proven experience leading or contributing to data platform modernization or migration projects (e.g., to Snowflake or AWS).
• Experience in the financial services industry is…