At Sparq, we help companies solve the right problems—not just build more technology.

We’re a modern product engineering partner blending strategy, craftsmanship, and speed to help organizations modernize confidently in the age of AI. From data ecosystems to digital products and AI acceleration, we turn complexity into clarity and ideas into impact.

If you’re driven to build what’s next, lead with empathy, and deliver excellence without ego, you’ll feel right at home at Sparq.

Why you will enjoy Mondays again:

• Opportunity to collaborate with a diverse group of colleagues in a fun, creative environment
• Progressive career journey and opportunity for advancement
• Continuous development through training, mentorship and certification programs
• Exposure to modern technologies across various industries in an agile environment
• Remote work

A Day in the Life:

• Design and evolve enterprise data architecture across lakehouse, data warehouse, pipeline, and semantic layers, ensuring scalability, performance, and alignment with enterprise standards
• Translate high-level architectural strategy into actionable technical plans, breaking work into epics, features, and sprint-ready stories for engineering teams
• Lead technical design discussions, proactively identifying dependencies, risks, and tradeoffs to drive efficient and predictable delivery
• Establish and enforce best practices for data modeling, pipeline design, data quality, and taxonomy across the platform
• Review architecture and code for complex data solutions, ensuring consistency, maintainability, and optimal performance
• Serve as a technical bridge across Data Engineering, Data Science, and Enterprise Architecture to ensure cohesive, end-to-end solutions
• Mentor engineers by providing architectural guidance and elevating system-level thinking across the team
• Design and build scalable data pipelines, dataflows, and semantic models using modern cloud-based data platforms (Microsoft Fabric / Azure)
• Contribute hands-on to high-impact initiatives, particularly where architecture and implementation are closely intertwined
• Support modernization efforts, including migration from on-prem SQL Server environments to cloud-based data platforms
• Optimize data processing workflows for performance, reliability, and cost efficiency using modern engineering patterns
• Partner with Data Scientists to productionize and operationalize machine learning models within enterprise data pipelines
• Participate in release planning and cross-team coordination to ensure aligned delivery across multiple initiatives
• Create and maintain clear, concise technical documentation covering architecture, standards, and key systems

What it takes:

• Deep expertise in modern data architectures, including lakehouse, data warehousing, data pipelines, and semantic modeling
• Strong experience with Microsoft Fabric and Azure data services (e.g., Synapse, Data Factory, Azure SQL, OneLake, etc.)
• Advanced proficiency in data engineering tools and languages (e.g., Python, SQL, Spark, notebooks, ETL/ELT frameworks)
• Demonstrated ability to define and implement architecture standards, design patterns, and best practices across data platforms
• Experience translating high-level architecture into deliverable work (epics, features, user stories) within Agile environments
• Strong understanding of data modeling, data governance, and data quality frameworks
• Experience designing and optimizing high-performance, scalable, and cost-efficient data pipelines
• Hands-on experience with cloud migration efforts, particularly transitioning from on-prem SQL Server environments to modern cloud platforms
• Familiarity with ML/AI integration into data platforms, including supporting production-ready model deployment
• Ability to operate as a technical leader across multiple teams, influencing without direct authority
• Strong communication skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical stakeholders
• Experience mentoring engineers and elevating overall engineering quality and consistency
• Ability to thrive in a hybrid role (architecture + hands-on delivery) within a fast-paced, evolving environment

Regardless of your specific role, we seek individuals who are excited to explore, adopt, and evangelize AI tools and methodologies. If you have experience in AI or a proven track record of rapidly learning and mentoring others on emerging tech, you’ll fit right in.

Equal Employment Opportunity Policy: Sparq is proud to offer equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic.

We are committed to providing equal employment opportunities and believe in an inclusive workplace. If you require reasonable accommodations to participate in the job application or interview process, please let us know by contacting recruiting@teamsparq.com

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