Data Engineer

Senior Data Engineer Location: Toronto, ON - Hybrid - (1 day per week at Onsite) Contract Length: 9 months with possibility of extension. We at Raise are hiring a Senior Data Engineer for one of our top clients. After establishing themselves as an industry leader, they’re now expanding their team to meet rising demand. We’re hiring right now; if you’re interested, apply below for your chance to join a great place to work. Responsibilities: Collaborate with stakeholders to deliver data models to address operational needs. Combine multiple data sources across all contact center platforms and applications to support advanced analytics products. Ingest massive volumes of structure and unstructured format data, model, transform and store it in a variety of data stores. Support the Senior Data Engineer in defining data quality metrics and processes to monitor data in production environment. Assist MIS & Data Analytics team with infrastructure development. Develop ETL/ELT for analytics solutions using Python, Spark, SQL and Power BI. Produce ad hoc analyses, deep-dives, and drill downs on specific issues, topics, or areas of opportunity (e.g. process improvements). Support the Senior Data Engineer in preparing reports and presentations to communicate findings to stakeholders. Assist in mentoring and up-skilling peers for advanced analytics. Streamline, enhance and automate existing products to create capacity for team to develop new solution. Candidate Requirements/Must Have Skills: 8- 10 years using python or other programming languages , package management, dependencies, and deployment. 8- 10 years using SQL for ETL and data analysis, flexibility on syntax (SQL server, PostgreSQL). 8- 10 years of data engineering experience working with cross-functional data teams. 8- 10 years of experience with data modelling, data warehousing and database design. 8- 10 years’ experience designing and building ETL/ELT, data pipelines, or data engineering solutions. Strong Experience with Linux tools and shell scripting. Nice-To-Have Skills: Experience with cloud architecture and the security (Azure, AWS, GCP). Experience and understanding of various ML techniques including NLP. Hands-on experience with Big Data ecosystem tools (e.g. Hadoop, Hive, Spark, BigQuery) and object storage (e.g. blob, MinIO, GCS). Understanding of Agile and Scrum methodologies and experience working in a Scrum environment (Jira and Confluence). Experience with Docker, CI/CD tools, and Airflow and Kubernetes. French and / or Spanish fluency an asset. Contact center experience an asset. Experience with telephony data (Avaya, Genesys) and WFM data (Verint, Aspect) an asset. Education: University degree in science, computer science, math, statistics, finance, economics, or another quantitative field, or equivalent experience.

Location: Toronto, CA

Posted Date: 10/5/2024