Data Architect

Core Qualifications

• Strong business acumen with the ability to translate complex data requirements into strategic architecture solutions across multiple domains.
• Proven leadership, communication, and advisory capabilities with a track record of influencing enterprise-level technology decisions and driving architectural standards.
• 10+ years of experience in data architecture, solution architecture, or similar senior technical roles.
• Deep expertise in modern data architectures such as data lakehouse, data warehouse, operational data stores, and streaming/event-driven patterns.
• Expertise in conceptual, logical, and physical data modeling, leveraging tools like Erwin to deliver scalable, enterprise-grade data models.
• Experience designing or advising on AI/ML and IoT architectures, ensuring seamless integration into enterprise data ecosystems.
• Extensive experience in architecture governance, including conducting design reviews and ensuring compliance with enterprise standards in large-scale environments.
• Strong knowledge of data security principles – RBAC, ABAC, encryption, tokenization.
• Comprehensive technical proficiency across cloud platforms, data engineering, security, observability, databases, and BI tools, including:

• Cloud Platforms: AWS (S3, Glue, Redshift, EMR, IAM, Lake Formation); GCP (Big Query, Dataflow, Pub/Sub).
• Data Engineering & Analytics:
  Databricks (Delta Lake, SQL, ML, Unity Catalog, Workflows).
• Observability & Operations:
  Datadog, Service Now.
• Databases:
  Enterprise RDBMS (Oracle, SQL Server, DB2);
  Cloud data stores (Snowflake, Dynamo
  
  DB, Big Query).
• BI Tools:
  Tableau, Alteryx, Power BI.
• Expert ability to assess architectural trade-offs, articulate design rationale, and align decisions with business objectives for both technical and non-technical stakeholders.

Additional Expertise That Strengthens Candidacy

• Proven experience architecting and managing solutions in multi-cloud or hybrid environments, ensuring interoperability and performance at scale.
• Demonstrated success leading legacy system modernization programs and executing complex cloud migration strategies.
• Proven ability to design and implement compliant data architectures for regulated industries, ensuring security and governance standards.
• Extensive experience mentoring and developing architects and engineering teams to elevate architectural maturity and best practices across the organization.
• Experience delivering data architecture solutions in automotive or manufacturing domains, with an understanding of industry-specific data challenges.

• Provide strategic advisory and governance for enterprise data initiatives by developing and enforcing architecture standards, patterns, and best practices aligned with organizational objectives.
• Participate in the Architecture Review Board (ARB) to review and approve data architecture designs across platforms and business domains.
• Evaluate end-to-end data lifecycle architectures—including ingestion, storage, processing, modeling, and consumption—for scalability, security, and cost-effectiveness.
• Identify architectural risks, gaps, and technical debt, and recommend mitigation strategies.
• Guide technology selection and trade-off decisions to ensure optimal solutions for business needs.
• Mentor engineering and analytics teams to improve architectural maturity and quality.
• Support solution decisions across cloud, on-premises, and hybrid ecosystems, ensuring interoperability and compliance.

• Deliver measurable outcomes, such as:
• Consistent delivery of high-quality, enterprise-grade data architectures.
• Reduction of risk and technical debt through effective governance and oversight.
• Enhanced compliance and security alignment across all data solutions.
• Accelerated delivery enabled by standardized patterns and clear architectural guidelines.