Databricks Architect designing and deploying enterprise cloud data platforms for Cuesta Partners’ consulting clients. Leading pipelines, governance, CI/CD, and client - facing technical delivery.
About the role
- Platform Architect designing AI-driven technology solutions for Benevity, helping companies take social action through technology. Leading enterprise architecture for large-scale data solutions across the organization.
Responsibilities
- Develop and maintain end-to-end tracks with our data and AI focus technology strategy and architectural portfolio
- Mentor engineers and technical leadership by providing clear patterns, ensuring adherence to architectural patterns, and offering hands-on guidance for complex implementations
- Lead architecture decisioning through Architecture Decision Records (ADRs), standards, and design reviews
- Oversee architectural reviews, code reviews, and system performance analysis to ensure quality standards and sustainable delivery momentum
- Foster a culture of collaboration, knowledge sharing, and continuous learning through mentorship, team collaboration, and workshops
- Enable governed data consumption through clear data contracts, curated datasets, and consistent serving patterns including domain marts
- Standardize end-to-end data flow patterns including ingestion, transformation, storage, serving, and retirement with repeatable templates
- Set platform standards for orchestration and reliability including SLAs, retries, idempotency, backfills, runbooks, and operational dashboards
- Establish enterprise data quality practices including critical data elements, quality rules, validation layers, monitoring, and issue triage workflows
- Drive governance-by-design by embedding metadata, lineage, classification, and ownership into platform patterns
- Drive adoption of AI governance architecture for agentic solutions including controls for data privacy and model lifecycle
- Define AIOps standards ensuring AI systems have traceability, quality measurement, incident response readiness, and cost guardrails
- Collaborate with stakeholders and product management to identify, prioritize, and mitigate technical risks and challenges
- Stay informed about industry regulations, security standards, and compliance requirements to ensure solutions meet necessary standards
Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
- 7+ years in software development methodologies, architecture, and implementation of large scale enterprise systems
- 4+ years focused on data engineering, data management, or data platform architecture and designing AI solutions including AIOps practices
- Structured problem solving to turn ambiguous requirements into scalable, low-cost solution patterns
- Ability to think strategically while paying close attention to technical details
- Proven experience building or evolving an enterprise data platform including standards and adoption across multiple teams
- Demonstrated ability to design governance-ready AI solutions including evaluation strategies, privacy safeguards, and auditability
- Strong expertise in system architecture, cloud computing, distributed systems, and integration technologies
- High bar for operational readiness, actionable documentation, and treating governance as a built-in platform feature
- Deep experience across modern data platform capabilities including AWS Glue, Step Functions, Airflow, dbt, Spark, and Snowflake
- Proficiency in programming and analytics using Python, SQL, and Jupyter Notebooks
- Experience with agentic frameworks such as LangChain, LlamaIndex, or LangGraph and AIOps tooling like LangFuse
- Familiarity with Agile development methodologies and the ability to adapt to a fast-paced environment
- Strong understanding of security principles, performance optimization, scalability, and reliability
- Demonstrated influence towards simplicity and repeatability in architecture.
Benefits
- Health insurance
- 401(k) matching
- Flexible working hours
- Paid time off
- Remote work options
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