Description:
KPMG Digital Toronto has an exciting opportunity for a Data Engineer, Consultant to join our team! This role will be a rewarding experience for you if you:
- Thrive on challenges and work best in a fast-paced environment where each day is different
- Work well in a project team environment and have strong collaboration and interpersonal skills
- Have a permanent "figure it out" mindset
What you will do
- Work closely with clients to understand key business issues.
- Gather and analyze requirements to develop impactful recommendations and solutions.
- Work in teams and individually to performance ETL (extract, transform and load) of data from a variety of databases, SQL, NoSQL, Hadoop, Neo4j, etc.
- Strong experience with large scale and/or distributed processing methodologies such as Storm, Spark or others.
- Review data quality and definitions and perform data cleansing and data management tasks.
- Work with the engagement team to translate business and analytics requirements into a data strategy for the engagement including ETL, data model and staging data for analysis
- Architect the data platform for scalability, repeatability and performance.
- Architect data pipelines to support streaming data, batch data, etc.
- Develop standards for data processes and automate routine tasks.
- Run queries for descriptive analytics and provide formatted result sets.
- Proactively contribute to the creation of presentation materials relating to data activities for stakeholder discussions.
- Support application testing and production implementation as required.
- Bridge the gap between technical platform needs and business issues.
- Enable overall solution and full-scope architecture design and build.
- Design software architecture following best practices after understanding customer enterprise environment requirements.
What you bring to the role
- University degree in computer engineering, mathematics, data science or related disciplines
- 2+ years of professional experience in a related field
- Strong experience working in teams to perform ETL (extract, transform and load) of data from a variety of databases from SQL, NoSQL, Hadoop, Neo4j, etc.
- Independent ability to review the data quality and data definitions, and perform data cleansing and data management tasks
- Experience working in a multi-disciplinary team to tack unstructured data processing problems across a diverse range of industries
- Experience in at least one major cloud service: AWS, MS Azure and GCP, microservices and serverless computing