Requisition ID: 232229
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
The Wealth Data engineering team within the Global Wealth Engineering (GWE) is the key team in meeting the operational data needs of the various stake holders within Wealth Management. The Data Engineer will play a key role in designing and implementing data solutions using Big Data, Hadoop (Cloudera) and Google cloud working closely with the enterprise data team and data architects, solution architects, business systems analyst and data engineers

NICE-TO-HAVE SKILLS:

• Understanding of Wealth business line and the various data domains required for building an end to end solution
  Location(s): Canada : Ontario : Toronto
  Scotiabank is a leading bank in the Americas. Guided by our purpose: “for every future”, we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
  At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted

IS THIS ROLE RIGHT FOR YOU? IN THIS ROLE YOU WILL:

• Leading development efforts in ingesting and transforming data from various sources. Working in the Big Data/ Hadoop environment, should be hands on in writing code, building scripts, writing specifications and responsible for end to end delivery of data in the Enterprise Data Lake environment
• Build distributed, reliable and scalable data pipelines to ingest and process data from multiple data sources
• Designing, building, operationalizing the data platform using Google Cloud Platform (GCP) data services such as DataProc, Dataflow, CloudSQL, BigQuery, CloudSpanner in combination with third parties such as Spark, Apache Beam/ composer, DBT, Cloud PubSub, Confluent Kafka, Cloud storage Cloud Functions & Github
• Designing and implementing data ingestion patterns that will support batch, streaming and API interface on both the Ingress and Egress.
• Working with a team of data engineers on developing framework and custom code using best practices that will meet the demanding performance requirements
• Contribute to the design and building of production data pipelines from data ingestion to consumption using GCP services, Java, Python, Scala, BigQuery, DBT, SQL etc.
• Experience using Cloud Dataflow using Java/Python for deploying streaming jobs in GCP as well as batch jobs using text/JSON files and writing them to BigQuery
• Development experience with industry ETL tools such as Talend, Informatica, or IBM DataStage.
• Building and managing data pipelines with a deep understanding of workflow orchestration, task scheduling and dependency management
• Provide end-to-end technical guidance and expertise on how to effectively use Google Cloud to build solutions; creatively applying cloud infrastructure and platform services to help solve business problems; and communicating these approaches to different business users
• Provide guidance on Implementing application logging, notification, jobs monitoring and performance monitoring

DO YOU HAVE THE SKILLS THAT WILL ENABLE YOU TO SUCCEED IN THIS ROLE? WE’D LOVE TO WORK WITH YOU IF YOU HAVE:

• 5+ years of experience in data engineering, performance optimization for large OLTP applications
• Experience with the primary managed data services within GCP, including DataProc, Dataflow, BigQuery/DBT, Cloud Spanner, Cloud SQL, Cloud Pub/Sub etc.
• Experience with Google Cloud Platform Databases (SQL, Spanner, PostgreSQL)
• Working experience in HQL
• Good knowledge of the concepts of Hadoop.
• Experience working with relational/NoSQL databases
• Experience with data streaming and technologies such as Kafka, Spark-streaming etc.
• Experience with Infrastructure as Code (IaC) practices and frameworks like Terraform
• Knowledge of Java microservices and Spring Boot
• Strong architecture knowledge with experience in providing technical solutions for cloud infrastructure.
• Working knowledge of developing and scaling JAVA REST services, using frameworks such as Spring
• Good communication and problem-solving skills. Ability to effectively convey ideas to business and technical teams