A Private Equity firm based in Toronto is looking for an Intermediate Data Engineer to perform OCR data extraction and work on ML projects
The Company is North America’s fastest growing Private Equity firm and just closed another $4.0 Billion fund. Five years ago, they were a team of 3 – now they’re 104+. With $9.2 Billion USD under management, they’re young, agile, and growing quickly.
This is a rare opportunity to join this powerhouse private equity firm – you are driven, you have a few years of work experience as a Data Engineer , and you want to put in the work in a firm where you will be rewarded financially and mentally.
• They hire the best of the best.
• Hustle, drive, and ability to adapt are the common traits of their team members.
• Onsite – 4 days a week.
Must Have Skills:
• 3+ years data extraction development using SQL and experience with Python building new BI product features
• Experience integrating, implementing, administering APIs
• 3+ years of experience in custom ETL design, implementation and maintenance
• Strong Financial industry knowledge
• Education that demonstrates a commitment to being the best of the best and continuous learning (Masters level)
Nice to have:
• Experience with Java
• Experience with RPA technology
• Experience with a Dashboard Tool like Tableau
Your challenge, if you choose to accept it:
• Assist with cloud architecture and infrastructure, using machine learning and data warehousing tools including Google Cloud Platform (GCP), Python, Big Query
• Develop enterprise wide solutions on our Google Cloud data warehousing platform that support business intelligence, reporting and analytical needs.
• Designing, building, and maintaining the business’s ETL pipeline and data warehouse
• Optimizing data warehouse performance to enable visual analytics tools such as Tableau and any other
• Applying automation and innovation on data platforms and any new development projects/initiatives aligned to business or organizational strategies
• Collaborating with various technology/business/project teams to understand business data and provide analysis and requirements to ensure the data design/development initiatives are in line with the planned design and standards
TECHNOLOGY BACKGROUND:
The organization is putting heavy emphasis on technology investment, and is using the latest and greatest in technology.
