Sr. Data & Analytics Architect

Data & AI Architecture

• Design and implement enterprise-scale data architectures supporting analytics, machine learning, and AI applications.
• Architect modern data platforms including data lakes, lakehouses, warehouses, and real-time pipelines.
• Define AI/ML solution architecture including model training, deployment, monitoring, and governance.
• Design and support dashboard development using PowerBI, Databricks, etc.

Cloud & Platform Engineering

• Lead architecture for data and AI workloads on cloud platforms (AWS, Azure, or GCP).
• Implement scalable pipelines using technologies such as Spark, Databricks or similar.
• Optimize system performance, scalability, security, and cost.

AI & Machine Learning Solutions

• Architect and guide development of AI-driven solutions including predictive analytics, NLP, recommendation systems, and generative AI applications.
• Support MLOps and AI lifecycle management including model deployment, monitoring, and versioning.

Enterprise Integration

• Design integrations between data platforms, operational systems, and AI services.
• Establish APIs, event-driven architectures, and data sharing frameworks.

Governance & Security

• Define and implement data governance, security, and compliance standards.
• Ensure adherence to privacy regulations and enterprise security frameworks.

Stakeholder Engagement

• Collaborate with business leaders, product teams, and engineering teams to translate business problems into technical solutions.
• Lead architecture reviews and provide technical guidance across multiple initiatives.

Leadership & Mentorship

• Mentor data engineers, ML engineers, and architects.
• Establish architecture standards, design patterns, and best practices.
• Influence strategic technology decisions across the organization.

• Base Salary Range: $165,000 - $185,000 Annually
• Annual Bonus Program
• Equity
• 401(k) Profit Sharing
• Medical, Dental, Vision & More!
• Final compensation will be determined based on experience and skills and may vary based on location.

• 10+ years of experience in data engineering, analytics, or platform architecture.
• 5+ years designing cloud-based data platforms and AI/ML solutions.
• Strong expertise with data architecture patterns (data lake, lakehouse, warehouse).
• Experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, or similar).
• Hands-on experience with big data technologies (Spark, Databricks, Hadoop ecosystem, etc.).
• Strong knowledge of SQL, Python, and distributed data systems.
• Experience implementing MLOps pipelines and model lifecycle management.
• Excellent communication and stakeholder management skills.
• Experience with Generative AI and LLM-based applications.
• Knowledge of data governance platforms and metadata management.
• Industry experience in retail, e-commerce, finance, or supply chain.
• Relevant certifications (AWS/Azure/GCP Architect, Databricks, Snowflake).
• Knowledge of SAP systems and data structures is a big plus in addition to other data platforms.

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