Software Engineer

• Own end-to-end delivery of data management features, ensuring on-time and high-quality output.
• Break down large initiatives into milestones, sprints, and actionable tasks.
• Coordinate work across engineering, data science, product, and infrastructure teams.
• Monitor progress, manage risks, and adjust plans when requirements evolve.
• Ensure architectural decisions align with data strategy, scalability, and reliability goals.
• Provide directions on Data modeling, Data pipelines (ETL/ELT), Data governance & quality frameworks, Metadata management, Data lineage tools
• API and platform integration
• Build, lead, and mentor a team of data engineers, software engineers, and data analysts.
• Facilitate career development, performance reviews, and skill-building.
• Create a culture of accountability, ownership, and continuous improvement.
• Resolve conflicts, remove blockers, and keep the team aligned on priorities.
• Work with product managers to define clear requirements and success metrics.
• Collaborate with business stakeholders on data needs, SLAs, and integration priorities.
• Communicate progress to executives and provide roadmap visibility.
• Manage expectations around delivery timelines, scope, and trade-offs
• Design, develop, test, and deploy data integration processes (batch or real-time) using tools such Data Factory, Databricks, Matillion, Airflow, Sqoop, etc.
• Create functional & technical documentation – e.g. ETL architecture documentation, unit testing plans and results, data integration specifications, data testing plans, etc.
• Provide a consultative approach with business users, asking questions to understand the business need and deriving the data flow, conceptual, logical, and physical data models based on those needs. Perform data analysis to validate data models and to confirm ability to meet business needs.
• May serve as project or DI lead, overseeing multiple consultants from various competencies
• Stays current with emerging and changing technologies to best recommend and implement beneficial technologies and approaches for Data Integration
• Ensures proper execution/creation of methodology, training, templates, resource plans and engagement review processes
• Coach team members to ensure understanding on projects and tasks, providing effective feedback (critical and positive) and promoting growth opportunities when appropriate.
• Coordinate and consult with the project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels
• Architect, design, develop and set direction for enterprise self-service analytic solutions, business intelligence reports, visualisations and best practice standards. Toolsets include but not limited to: SQL Server Analysis and Reporting Services, Microsoft Power BI, Tableau and Qlik.
• Work with report team to identify, design and implement a reporting user experience that is consistent and intuitive across environments, across report methods, defines security and meets usability and scalability best practices.

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