Senior Data Engineer — ETL Pipelines & AI-Ready Data

RBC; Mississauga; On-site; CAD 80,000 - 130,000; Full time

Benefits offered by this job

Total rewards program

Flexible benefits

Career development opportunities

Job summary

RBC Insurance is seeking a data engineer/analyst to build data pipelines and robust ETL/ELT processes for handling large-scale financial data. The role focuses on SQL and Python development, and cloud tools across Snowflake, Databricks, AWS, Azure, and GCP.

The candidate will contribute to enterprise DAaaS initiatives, support LLM self-service projects, ensure data governance, and collaborate with data architects to design robust data models.

Qualifications

• 3+ years of experience in SQL and Python.
• Experience with Snowflake, Databricks, AWS, Azure, or GCP.
• Experience transforming enterprise-level data at scale with billions of records.
• Strong data warehousing and data modelling knowledge.
• CS/engineering degree or equivalent experience.

Responsibilities

• Build data pipelines and reports transforming financial data reporting.
• Build and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop and optimize complex SQL queries, stored procedures, and scripts.
• Develop Python programs and perform advanced data analytics.
• Contribute to enterprise DAaaS initiatives.
• Work on projects enabling LLM self-service capabilities for business users.
• Ensure data integrity, quality, and governance throughout transformation.
• Collaborate with Data Architects and Analysts on data models and transformations.

Skills

SQL

Python

Analytical thinking

Communication skills

Education

Computer Science or Engineering degree, or equivalent experience

Tools

Snowflake

Databricks

AWS

Azure

GCP

Apache Airflow

DBT

Job description

RBC Insurance is seeking a data engineer/analyst to build data pipelines and robust ETL/ELT processes for handling large-scale financial data. The role focuses on SQL and Python development, and cloud tools across Snowflake, Databricks, AWS, Azure, and GCP.

The candidate will contribute to enterprise DAaaS initiatives, support LLM self-service projects, ensure data governance, and collaborate with data architects to design robust data models.