Principal Data Architect

Principal Data Architect

Description -

We are seeking a Data Engineering Architect who will lead both enterprise data platform architecture and data strategy to enable scalable AI/ML, telemetry analytics, and business intelligence solutions.

This role goes beyond traditional data engineering, requiring end-to-end ownership of data ecosystems, from ingestion to insights, and the ability to translate business priorities into scalable, AI-ready data strategy.

You will partner with Data Science, AI, teams to design future-ready data platforms, industrialize ML pipelines, and drive data as a strategic asset across the organization.

Key Responsibilities

Data Architecture Strategy

• Design the enterprise-wide blueprint for how data is stored, integrated, accessed, and governed

• Manage the technical platforms that enable downstream insights, solutions, etc

• Design PS Quality data warehouses / data lakes

• Determine architectural patterns (e.g., medallion architecture, data mesh, data fabric)

• Establish data standards and automated interoperability rules

Data Architecture & Platform Leadership

• Designing data warehouses / data lakes that meets Quality Business Requirements

• Define and implement enterprise-grade data architectures (batch, streaming, real-time) for large-scale structured and unstructured data.

• Design scalable, secure, and high-performance data platforms supporting BI, advanced analytics, and AI/ML use cases.

• Establish data modeling standards, and reusable frameworks across the organization.

Data Strategy & Transformation

• Lead enterprise data strategy, aligning data initiatives with business, AI, and digital transformation goals.

• Identify and prioritize high-value analytics and AI opportunities leveraging telemetry, operational, and product data.

• Drive data monetization, standardization, and governance frameworks.

• Define roadmap for modern data stack adoption (cloud-native, lakehouse, streaming, GenAI-ready architectures).

AI/ML Enablement & Industrialization

• Partner closely with Data Scientists to productionize ML/AI models into scalable systems.

• Build and optimize data pipelines, feature engineering frameworks, and MLOps workflows.

Engineering Execution & Innovation

• Lead the design, development, and deployment of complex data pipelines and distributed systems.

• Drive adoption of new technologies (GenAI, agentic systems, streaming architectures, data mesh).

• Ensure solutions meet performance, reliability, and cost optimization goals.

Governance, Security & Compliance

• Ensure adherence to data governance, privacy, security, and compliance standards in alignment with HP Cybersecurity and privacy guidlines

• Maintain master data management, access controls, audits, metadata, management, and data hierarchy

• Establish data quality frameworks, lineage, observability, and monitoring mechanisms.

• Implement best practices across data lifecycle management.

Cross-Functional Leadership & Influence

• Influence executive leadership, architecture boards, and cross-functional stakeholders on data strategy decisions.

• Act as a thought leader in data engineering and AI data ecosystems.

• Represent the organization in industry forums, publications, and innovation initiatives.

Business Alignment

• Translate business goals into platform capabilities

  • Faster automated analytics

  • Enhanced AI/ML readiness

  • Self-Service Tools

  • Operational Reporting

  • Enable data-driven decision making

Technical Expertise

• Strong experience in:

  • Cloud platforms: AWS, Azure (data services, analytics, storage)

  • Data platforms: Data Lakes, Lakehouse, Data Warehousing

  • ETL/ELT and pipeline orchestration

• Programming:

  • Python, SQL (mandatory)

  • Scala/Java (good to have)

• Experience with:

  • Streaming and real-time data systems

  • Data modeling and governance