Data Transformation Specialist

Reporting to the Manager, Data Science & Operations, the Data Transformation Specialist will help build, scale, and maintain MPI’s business intelligence and data science platform. The role will scale the corporation’s cloud and on-premises infrastructure, improve tools used by analysts and data scientists, streamline data feeds processes, and help improve data quality.

This Data Transformation Specialist plays a key role in elevating the business intelligence and data science delivery by building reliable pipelines and infrastructure to help the team improve modelling efficiency and consistency of data.

• Contributes to data pipelines by implementing a solid, robust, extensible design that supports key business flows.
• Performs data transformations to populate data-hub, data-lake, data warehouse, reporting databases and downstream data marts.
• Identifies technical requirements and delivers solutions by establishing efficient design and programming patterns that meet Service Level Agreements (SLAs) and help manage the data platform.
• Responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise.
• Designs, integrates, and documents technical components for seamless data extraction and analysis.
• Presents insights on data and its quality via presentations, visualizations, and whitepapers.
• Actively promotes automation of data quality, proposes, and implements solutions.
• Supports the corporation’s broader technical and operational requirements by adopting best practices in our data systems.
• Works in a team environment, interacting with multiple groups daily, within the department, as well as throughout the corporation.

• Works with business stakeholders to establish an understanding of the business and determine the data needs of the business.
• Communicates challenges and requirements to subject matter experts and clients, providing clear objectives over estimated timeline.
• Facilitates effective communication between business stakeholders and technology resources. Translates complex technology information into simple, clear, and accurate language to ensure understanding by stakeholders.
• Provides training to MPI system users, as required.
• Remains up to date on recent technologies that maximize the speed, performance, and access to data for analytics and machine learning and reducing costs.
• Responds to ad-hoc client requests.
• Leads projects from conception to completion and provides leadership to project resources.
• Provides training on data modelling and on the maintenance of data quality to analysts and project resources.
• Focuses on continuous learning, experimenting, applying, and contributing towards cutting edge open-source data technologies and software.
• Performs other duties as assigned.

• Five years of experience in data management, data engineering, and analytics, including data architecture, data integration, data warehousing, and cloud-based analytics solutions.
  • Within the above experience, at least three years of experience in data management disciplines such as data architecture, data integration, data warehousing, or analytics.
  • Two years of experience designing, implementing, and supporting data integration, data engineering, data warehousing, and analytics solutions using Microsoft’s cloud analytics platforms and services.
• The following are considered assets:
  • Experience in a leadership capacity.
  • Experience with virtualization in an enterprise environment.
  • Experience in the insurance or finance industry.
  • Experience with AWS, GCP, Snowflake, or other cloud data platforms.

• Working knowledge of Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory, PowerBI, and Azure Data Lake technologies.
• Working knowledge of architecting efficient framework and optimization designs for analytics platforms, data warehouse design, virtualization, pipelines, ELT, ETL, SSIS packages.
• Designs and implements medallion architecture, including bronze, silver, and gold data layers.
• Intermediate knowledge of big data, distributed computing, data pipelines, dimensional modelling, columnar and row-based databases, data visualization, machine learning, and data layer designs.
• Strong knowledge of Python, and high proficiency to design and develop ELT pipelines using Spark and Databricks.

• Working knowledge of PowerBI, Business Objects, or similar Business Intelligence tools.
• Working knowledge of handling log or event streaming data sources.
• Knowledge of Data Science and Machine Learning concepts.
• Performs root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

• Working knowledge of DevOps, DataOps, and Git.
• Working knowledge of container technologies e.g., Docker, and Kubernetes.
• Knowledge of additional programming languages (e.g., Java, .Net) and ETL tools (e.g., SSIS).
• Working knowledge of writing Stored Procedures and developing in tools such as Microsoft SQL Server.
• Advanced written and oral communications skills to convey technical information in a clear, concise, and understandable manner for both technical and non-technical audiences.
• Advanced problem solving and analytical skills.
• Works with accuracy and attention to detail.
• Manages conflicting priorities and adapt to changing circumstances.
• Interacts with all levels of staff and management in an efficient and courteous manner.