Data and Analytics Engineer

Summary: • Experience Level: Level 3 (senior): 5-7 years • Open positions: 1 • Location: Montreal • Work Mode: Day 1 onboarding onsite / in office presence 3x week Responsibilities: • Hands-on development, data pipeline creation, and collaboration with stakeholders across the organization. • Drive decision-making and business insights through specialist data analysis and expertise. • Craft data pipelines, implement data models, and optimize data processes for improved data accuracy and accessibility. • Apply machine learning and AI-based techniques. Requirements: • Experience in data engineering or a related field. • Design and implement data pipelines and workflows to support analytics and reporting needs. • Develop interactive dashboards and reports using visualization tools like Power BI and Tableau. • Collaborate with business stakeholders to understand requirements and translate them into data models and visualizations. • Utilize Dataiku and other analytics platforms for data preparation, machine learning workflows, and advanced analytics. • Ensure data quality, integrity, and security across all analytics solutions. • Optimize performance of dashboards and queries for large datasets. • Stay updated on emerging trends in data analytics and visualization technologies. • Experience working on Snowflake and Databricks (Min one of the two). • Knowledge of database systems (SQL and NoSQL). • Experience on Snowflake Cortex appreciated. • Familiarity with cloud platforms (AWS, Azure) and their data services. • Experience using Jupyter notebooks for data exploration, analysis, and visualization. • Excellent communication and collaboration skills. • Ability to work independently and as part of a geographically distributed team. Preferred Skills: • Familiarity with programming skills in Python. • Experience with data warehousing concepts and technologies. • Familiarity with data governance and security best practices (e.g., data access control, data masking). • Experience with Agile methodologies. • Familiarity with data catalog and metadata management tools (e.g., Collibra). • Familiarity with CI/CD pipelines and DevOps practices. Benefits: • Integrity and ownership, good team player. • Ability to work under time and resource dependencies and constraints. • Ability to find simple and effective solutions. • High degree of motivation to expand technical and business knowledge. Skills: Access Control, Agile Programming Methodologies, Amazon Web Services (AWS), Artificial Intelligence (AI), Best Practices, Cloud Computing, Communication Skills, Computer Programming, Continuous Deployment/Delivery, Continuous Integration, Data Analysis, Data Management, Data Modeling, Data Processing, Data Quality, Data Sets, Data Visualization, Data Warehousing, Database Technology, DevOps, Information/Data Security (InfoSec), Machine Learning, Metadata, Microsoft Windows Azure, NoSQL, Onboarding, Performance Tuning/Optimization, Power BI, Process Improvement, Python Programming/Scripting Language, Reporting Dashboards, SQL (Structured Query Language), Sales Pipeline, Security Analysis, Tableau, Team Player, Trend Analysis About the Company: Axelon

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