Job Title: Data Analytics Specialist
Duration: 11 months (Maximum Extension Term: 12 months)
Location: Edmonton, AB (Resource will work remotely, though must be available for onsite meetings when required.)
Description:
Project Name: Data Projects - Various
Scope:
Reporting to the Manager, Data Product Delivery, the ideal candidate will be responsible for orchestrating and implementing robust ETL pipelines for different data product builds. The role requires incorporating CI/CD best practices while demonstrating strong commitment to data security and compliance.
Duties:
• Lead or be part of a team responsible for the generalizable extraction of knowledge from data by applying various techniques and theories including machine learning, computer programming, statistics, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high-performance computing.
• Design, orchestrate and develop high-performance and robust ETL pipelines leveraging cloud native tools.
• Integrate DevOps practices to the development workflow using CI/CD best practices.
• Build and optimize data warehouses, data lakes, ensuring efficient storage and retrieval system for analytical needs.
• Provide expertise in data modelling (star or snowflake schema) to enhance data flow and query performance, supporting Data Product Delivery.
• Hands – on experience with building and managing data products, from initial concept through to deployment while ensuring alignment with business objectives and user requirements.
• Understanding of Data Product Market place and its key Data Governance components including Data Quality, Meta data, Data lineage, accessibility and standardization.
• Demonstrate strong commitment to Data Security and Compliance to protect sensitive information and enforce data governance in enterprise platforms (access control, security policies across platforms etc.).
• Work across a myriad of technology stacks in Azure, Cloudera, Snowflake, PowerBI etc.
• Experience with Python and SQL in the context of building data pipelines
• Experience working with Big Data technologies
• Experience in Data Analytics
• Design and create dashboards and custom reporting with various data sources and inputs.
• Apply skills to provide insights, support decision-making and facilitate strategic business planning across the department.
• Provide executives and decision makers a deeper understanding of their operations, transactions, services and information required for them to identify new opportunities that can only be uncovered through analytics.
• Provide depth and insight to data produced by the various teams and transform them into meaningful analytics for decision making.
• Ensure delivery processes are robust, of high quality and repeatable.
• Provide strategic agility and the ability to make sense of large amounts of disparate data to tell a cohesive story focused on key strategic decision-making for executives.
• Integrate both quantitative and qualitative data to create business insights.
• Analyze data and prepare information results.
• Gather and document client requirements.
• Design and construct information products.
• Capture business and technical metadata for information products.
• Establish and operate control processes including schedule management, status reporting, issues, risk, and change management at the program level.
• Escalate issues and risks, as appropriate.
• Work within a multi-vendor/staff environment.
Experience building high performance, scalable and robust ETL pipelines in distributed clusters
Experience in creating Microsoft-SQL database solutions.
Experience in data analytics or data science.
Experience integrating DevOps practices to the development workflow using CI/CD best practices
Experience using analytical and problem solving skills to plan and design creative solutions
Experience with dimensional modeling techniques.
Experience with Python development
Experience with relational database modeling techniques.
Experience working in a data warehouse/business intelligence or relevant data environment in either a development or support role.