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Data Engineer

RBC is Canada's largest bank and one of the largest banks globally by market capitalization, serving over 16 million clients across Canada, the US, and 34 other countries.
Data
Mid-Level Software Engineer
In-Person
5,000+ Employees
4+ years of experience
Finance

Description For Data Engineer

RBC, Canada's largest bank, is seeking a Data Engineer to join their Investor Services Data Engineering team. This role combines technical expertise with strategic thinking to implement data architecture best practices across the global organization. The position requires strong skills in data engineering, cloud technologies, and API development, with a focus on building real-time data pipelines and supporting advanced analytics needs. The ideal candidate will have 4+ years of experience with technologies like Python, PySpark, Databricks, and Azure cloud services. Working in an agile environment, you'll collaborate with data scientists, process engineers, and business stakeholders to deliver robust data solutions. RBC offers a comprehensive benefits package, including competitive compensation, flexible work arrangements, and professional development opportunities. The role is based in Toronto and offers the chance to work with a dynamic team while contributing to one of the world's largest financial institutions.

Last updated 24 days ago

Responsibilities For Data Engineer

  • Build real-time data pipelines (inbound, outbound) through container-based solutions
  • Integrate data with Cloud based platforms, publish data through APIs and Portal
  • Participate in Data curation requirements and support Data and Digital needs
  • Evaluate current state of data access control regarding authentication, authorization and encryption practices
  • Work in an agile team of Data Engineers, Developers and RBC business stakeholders
  • Collaborate with data scientists, process engineers and business stakeholders on requirement gathering

Requirements For Data Engineer

Python
Node.js
MongoDB
PostgreSQL
  • 4+ years of hands on experience in data engineering
  • Experience with Python, PySpark, Databricks, Airflow, Kafka, MS SQL Server, Elastic search stack
  • Cloud and Containers: Azure (ADLS2, Azure Data bricks), Open shift, Docker
  • SQL/Database: Microsoft SQL Server, Azure SQL, Stored procedures
  • API: Node.JS, Apigee
  • Portal/analytics solutions: Angular
  • Security frameworks: LDAP, Kerberos, OAuth 2.0, Vault integration
  • Strong knowledge of algorithms and data structures

Benefits For Data Engineer

Medical Insurance
401k
  • Comprehensive Total Rewards Program including bonuses and flexible benefits
  • Competitive compensation and stock where applicable
  • World-class training program in financial services
  • Flexible work/life balance options
  • Leaders who support development through coaching
  • Opportunities for challenging work

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