DATA ENGINEER

at  SureWerx

SKILLS & QUALIFICATIONS:

• A bachelor’s degree in computer science or mathematics, or a related field is typically required. A master’s degree or relevant certifications can be advantageous.
• Proven experience (typically 5-7 years) as a Data Engineer, with strong knowledge of data modeling and design, SQL development and database administration.
• Strong experience in cloud infrastructure particularly Azure Synapse
• Experience with RESTful APIs, PostgreSQL and Azure Blob
• Demonstrated experience Power BI implementations.
• Strong analytical and problem-solving skills
• Excellent written and verbal communication and interpersonal skills to collaborate with cross-functional teams, stakeholders, and vendors. Ability to present complex information clearly and concisely.
• Ability to create and maintain detailed documentation for technical and non-technical audiences.
• Collaborative and adaptable, able to work effectively within a small team and adapt to changing business needs.
  SureWerx is committed to employment equity, supports diversity in the workplace and encourages application from all qualified individuals including women, members of visible minorities, Aboriginal peoples and persons with disabilities. Personal data provided by job applicants will be used strictly in accordance with our personal data policy and for recruitment purposes only. A copy of our Personal Information Collection Statement will be provided upon request by contacting our Privacy Officer.

• Data Modeling: Design and create data models that define how data should be structured, stored, and accessed, including conceptual, logical, and physical data models.
• Data Storage Systems: Maintain (and build where needed) data storage systems and policies. Continuously monitor and optimize functionality while balancing costs and storage.
• ETL (Extract, Transform, Load) Processes: Create and manage ETL processes to extract, transform, and load data from various sources into the data lake.
• Data Security: Monitor security software. Enforce data security policies and work closely with IT teams to design data security architectures.
• Data Architecture Framework: Visualize and develop the data management framework, standards and principles. Implement data architecture improvements, leveraging technology and best practices to drive efficiency and effectiveness. The defined framework must align with the SureWerx business model and enable advanced analytics and data science applications.
• Data Administration Policies: Develop and implement data administration policies including recovery and security.
• Compliance and Regulations: Ensure that data practices comply with relevant data protection and privacy regulations, such as GDPR.
• Documentation: Create and maintain comprehensive documentation, including functional specifications, reference architecture, system design, data dictionaries and process flows which represent data entities and their relationships, data sources, data pipelines and integrations.
• Requirements: Collaborate with key stakeholders to understand current and future business requirements. Translate business requirements into technical specifications including integrations, transformations, databases and data warehouses.
• Data Analysis and Mapping: Analyze data and perform data mapping to ensure smooth data integration between systems.
• Reporting: Preparing monitoring reports for managers
• Vendor Interaction: Participate in the evaluation and selection of data platforms, tools and services that support the data architecture strategy. Communicate with software vendors to understand product capabilities, updates, and to resolve technical issues.
• Continuous Improvement: Identify opportunities for process improvement and system enhancements to optimize functionality by monitoring and assessing the impact of emerging technologies and industry trends.
• Project planning: Assist in project planning and project scope sessions to ensure compliance to the project charter and implementation plans.
• System Testing: Develop test plans, conduct system and quality assurance testing, and coordinate user acceptance testing (UAT) to ensure the systems meet business requirements and functions correctly.
• Daily Support: provide ongoing support for data warehouse and integrations by monitoring status on issues, troubleshooting, root cause analysis, resolving technical issues and system defects, testing and monitoring of solutions.
• Data Governance: Support in the establishment of data governance policies, standards, and procedures (including Master Data Management) to ensure data quality, security, and compliance with relevant regulations and industry best practices.