Typical Day in Role:
• 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 of data engineering experience working with cross-functional data teams
• 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 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.