3 days ago
Vancouver, CanadaSenior
Responsibilities
- Design, build, and maintain batch and near-real-time ETL/ELT pipelines into Snowflake.
- Develop and optimize Informatica mappings, task flows, and transformations using IICS/IDMC or PowerCenter.
- Manage and tune Snowflake environments, including query optimization, workload management, virtual warehouse sizing, and cost optimization.
- Develop reusable Python components, frameworks, and PySpark scripts for data processing and validation.
- Implement dimensional models, star and snowflake schemas, and Slowly Changing Dimensions Type 1 and Type 2.
- Establish automated Git-based deployment pipelines for database schemas, Python code, and Informatica assets.
- Implement data quality checks, reconciliation processes, audit controls, and end-to-end data lineage.
- Partner with architecture, business intelligence, and data science teams to deliver scalable technical solutions.
- Mentor junior engineers and promote engineering best practices.
Requirements
- 7–10+ years of professional experience in data engineering, ETL development, and enterprise data warehousing.
- At least 5 years of hands-on Informatica PowerCenter or Informatica Cloud development experience.
- At least 5 years of deep Snowflake expertise, including SnowSQL, Snowpark for Python, and native cloud loading.
- Advanced Python proficiency, including Pandas or PySpark, and expert SQL development skills covering stored procedures, analytical functions, and performance tuning.
- Strong familiarity with AWS or Microsoft Azure cloud ecosystems.
- Experience with Git and automated deployment tools such as Azure DevOps or GitHub Actions.
- Strong problem-solving, analytical, communication, and cross-functional collaboration skills.
- Snowflake Certified Core Engineer or Informatica Cloud Data Integration Specialist certification is preferred.
- Experience with AWS, Azure, or GCP, and exposure to big data tools such as Spark or Kafka, are preferred.
- Understanding of data security and compliance is preferred.
- Experience preparing and optimizing datasets for machine learning and AI initiatives is preferred.
Benefits
- Comprehensive total rewards program with competitive compensation, bonuses, and flexible benefits.
- Coaching, career advancement opportunities, learning resources, and career development support.
- Opportunity to influence RBC’s data and technology strategy and take on greater technical leadership responsibilities.
- Collaborative, high-performing team working on enterprise-scale challenges.
- Full-time, regular salaried position based in Vancouver, Canada, with 37.5 hours per week.
Tech Stack
Apache KafkaApache SparkAWSAzureDjangoFastAPIFlaskGitGitHub ActionsGoogle Cloud PlatformInformaticaLinuxPandasPythonSnowflakeSQL
Categories
Data Engineering
About RBC
Royal Bank of Canada (RBC) provides personal and commercial banking, payments, mortgages, investing, wealth management, insurance, and capital markets services to consumers, businesses, and institutions. The public company, headquartered in Toronto and founded in 1864, serves more than 17 million clients across Canada, the U.S., and other global markets. Revenue comes from interest income, fees, advisory, and trading across its diversified financial services businesses, and it is Canada’s largest bank by market capitalization.