Senior Manager, Data Engineer

Key Skills

Amazon Simple Storage Service (S3), Apache Hadoop, Big Data Technology, Data Warehousing, Github, Java Programming, Neo4J, Software Development, SPARK Programming, SQL

Job Description

What is the opportunity?

As part of the Enterprise Payment’s Decision Management team, you will generate value by transforming raw data from a complex array of source systems into user-friendly data assets which will be used by data and insights analysts. You will develop, test, deploy, and maintain software to create complete and accurate data, using a variety of big data platforms, languages and tools, including Hadoop, Spark, Scala, and Git. You will develop recommendations for new ways to improve data quality throughout the data transformation lifecycle and play a key role in driving superior business results, by providing key strategic insights and recommendations on new and existing business opportunities, by building and operating a scalable platform for reporting, analytics, and data science.

To succeed you have extensive Data Engineering experience with a track record of liberating and strengthening data capabilities, deeper insights and better data driven business decisions.

What will you do?

• Analyze data sources, evaluate, develop, test, and deploy software to generate data assets (relational, graph, other) that can be consumed and re-used by our data analysis and reporting team

• Work with big data, graph, and cloud technologies such as Spark, Hadoop, Hive, Neo4j, S3, EMR, EC2, Lambda, and Kafka

• Work closely with stakeholders to ensure successful data asset design and development

• Join data across multiple data environments, such as HDFS, S3 and Data Warehouses, using complex optimized queries

• Use Scala, Cypher, Spark, GitHub, Maven, Jenkins and Airflow to develop and deploy automated data-producing software packages

• Good knowledge of popular data standards and formats (JSON, XML, Parquet, Avro, etc.)

• Create software artifacts and patterns for reuse within the enterprise

• Building and supporting ETL pipelines in Python using PySpark and Apache Airflow are produced with the highest quality standards, metadata and validated for completeness and accuracy for reporting, data science, analytics, and ad-hoc querying

• Help develop new solutions for batch and real-time data and analytics use cases

• Help improve data management processes - acquiring, transforming and storing massive volumes of structured and unstructured data

• Use deep Cards and Payments data domain knowledge to independently lead the data engineering and analytics process to identify valuable and innovative insights

• Constantly seek out better ways to do things, new tools, new technologies, new processes to meet business needs

• Work on both transformational and BAU projects delivering new value while also maintaining existing processes

• Stakeholder Consultancy - Manage relationships with key business stakeholders, ability to digest complex problems and organize into achievable milestones. Manages stakeholder expectations and keeps them up-to-date with project statuses.

• Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to problems that can be complex and non-routine

What do you need to succeed?

Must have:

• Bachelors in Computer Science, Software Engineering, Mathematics, or other STEM majors. Masters/PhD considered an asset.

• Professional software development experience with Scala, Spark, Hadoop, Neo4j, Java, Linux, and SQL

• 3+ years of experience in the big data ecosystem, with Hadoop (Pig, Hive, HDFS), Apache Spark, and NoSQL/SQL databases

• Experience using Git and Maven while collaborating on a software development team

• Experience using ETL big data pipelines (Apache Airflow), knowledge of CI workflows and build/test automation

• 5+ years of professional work experience in Data Analytics / Data Science / Business Analytics

• Advanced programming skills in one or more of the following languages: Python or R

• Strong core competency in SQL. Experience in writing complex SQL queries to extract and integrate data from multiple database source

• Ability to perform complex data analysis on large volumes of data and present findings to business stakeholders

Nice to have:

• Professional experience with Snowflake on Azure or AWS Cloud

• Knowledge of credit cards, payments and/or Banking products/data

• Experience with other data analytics and visualization tools such as Tableau

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• Ability to make a difference and lasting impact

• Work in a dynamic, collaborative, progressive, and high-performing team

• Opportunities to do challenging work

Job Skills

Apache Hadoop, Big Data, Big Data Management, Big Data Platforms, Business, Business Needs, Cloud Computing, Data Analysis, Database Development, Data Mining, Data Quality, Data Transformation, Data Warehousing (DW), ETL Pipelines, ETL Processing, Git, GitHub, Group Problem Solving, JSON, Maven, PySpark, Quality Management, Requirements Analysis

Additional Job Details

Address:

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City:

TORONTO

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

PERSONAL & COMMERCIAL BANKING

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2025-02-18

Application Deadline:

2025-02-28

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Inclusion and Equal Opportunity Employment

At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work. We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.

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We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.

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