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:
Sparq is looking for a Data Architecture & Strategy Professional to lead the design and execution of their next-generation industrial monitoring platform. This role combines hands-on architectural leadership with strategic guidance to ensure our solutions deliver measurable value through reliable, scalable, and AI-enabled data systems.
You will define the data and AI foundation for processing EMI, ESA, and vibration waveform data across industrial assets such as generators, pumps, motors, and transformers. You will work closely with stakeholders to align architectures with business objectives, governance frameworks, and deployment requirements across cloud, on-premise, and air-gapped environments. Your leadership will ensure our platform not only works technically, but also drives adoption, compliance, and long-term strategic growth.
Key Responsibilities:
Architecture & Roadmap Development
- Lead the design of scalable data architectures across Azure, Databricks, Unity Catalog, MLflow, AKS, Docker, and Postgres in cloud and on-prem architectures
- Define strategic roadmaps for handling high-throughput waveform data, anomaly detection pipelines, and hybrid deployments.
- Build architectural blueprints that balance performance, security, and portability across cloud, private cloud, and air-gapped environments.
Client Engagement & Strategic Alignment
- Collaborate directly with client stakeholders to align architecture with predictive maintenance and asset reliability outcomes.
- Translate business goals into data-driven strategies that support measurable ROI.
- Provide thought leadership on how data and AI can transform asset monitoring practices.
Governance & Compliance
- Work with the Databricks Engineer to establish governance, lineage, and validation frameworks using Unity Catalog to ensure data quality and trust.
- Design architectures that meet stringent compliance and security requirements across regulated industries.
- Define data ownership models and ensure governance practices extend seamlessly across deployment environments.
AI & Innovation
- Integrate ONNX-based anomaly detection models into data pipelines, enabling real-time and batch diagnostics.
- Collaborate with data science teams to optimize model deployment for industrial-scale sensor data.
- Stay on the forefront of AI, IoT, and industrial monitoring trends, driving continuous innovation in predictive insights.
Delivery Excellence
- Oversee architecture implementation and ensure systems are delivered with high reliability, scalability, and efficiency.
- Guide engineers in adopting best practices for containerization, orchestration, and hybrid deployment.
- Partner with internal teams to ensure solution consistency across nearshore and onshore resources.
Business Development & Thought Leadership
- Support client conversations with architectural insight and strategic perspective.
- Provide thought leadership on the intersection of AI, architecture, and strategy.
Key Qualifications:
- 12+ years in data architecture, engineering, or analytics roles, with at least 5 years in a leadership capacity.
- Proven track record designing and deploying hybrid architectures across Azure, Databricks, Unity Catalog, MLflow, AKS, and Docker.
- Expertise in ingesting, processing, and analyzing sensor/waveform data at scale
- Hands-on experience deploying AI/ML models with ONNX in industrial or IoT settings.
- Strong understanding of data governance, compliance, and lineage frameworks.
- Exceptional communication skills across executive and technical audiences.
- Experience supporting pre-sales and client engagements with architectural leadership.
- Entrepreneurial mindset with a passion for innovation in industrial monitoring and predictive AI.
Nice to Have:
- Hands-on familiarity with data engineering stacks (Databricks, CosmosDB, and Kafka) and BI/semantic layers (Power BI, or other BI platforms).
- Experience with ML platforms (feature stores, model registries, CI/CD for ML, monitoring/drift).
- Knowledge of responsible AI practices (evaluation frameworks, red-teaming, model cards).
- Prior experience leading distributed teams across U.S. + LATAM .
- Domain experience in (BFSI, Healthcare, Transportation & Logistics, Property, Hospitality).
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.
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