Senior Cloud Data Architect

Boeing • Arlington, VA

7d • Onsite

About The Position

The Boeing Company’s Talent Analytics and Innovations team is currently seeking a Senior Cloud Data Architect to join our team in Arlington, VA. This position will design and build a scalable, secure, and governed cloud data platform to support HR analytics, reporting, workforce intelligence, and AI/ML use cases. This role partners with HR, HR IT, Data Science, Analytics, IT/Security, and Data Governance to translate HR requirements into platform architecture, enable data pipelines and catalogs, and ensure data quality, lineage, and compliance. The ideal candidate is a strong communicator who effectively translates complex technical architecture into clear, understandable terms for business stakeholders and HR partners. They are highly collaborative, working seamlessly across HR, Data Science, IT, Security, and Legal teams to drive alignment and results. With a pragmatic and product-minded approach, they skillfully balance speed, cost, scalability, and governance to deliver impactful solutions. Additionally, they have a strong focus on mentoring and team enablement, building reusable patterns and empowering cross-functional teams to achieve their goals efficiently.

Requirements

• 7+ years of data engineering/architecture experience, including 3+ years designing cloud data platforms.
• Experience supporting HR, People Analytics, or enterprise analytics use-cases

Nice To Haves

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
• Certifications in cloud platforms (AWS Certified Solutions Architect, Azure Data Engineer, GCP Professional Data Engineer) or relevant architecture/data engineering credentials
• Experience implementing feature stores and production ML data pipelines in enterprise environments
• Experience working with HR systems (Workday, SuccessFactors, ADP) or People Analytics teams
• Experience with public cloud platforms (AWS, Azure, or GCP) and core services for data engineering (storage, compute, serverless, IAM)
• Experience with data lakehouse or modern data platform architectures (e.g., Delta Lake, Databricks, Snowflake, BigQuery, Synapse)
• Experience in data ingestion and processing frameworks (Spark, Dataproc, Glue, Dataflow, Flink, Kafka, Kinesis)
• Experience with ETL/ELT design, orchestration tools (Airflow, Prefect, Step Functions), and workflow automation
• Experience with data cataloging and governance tools (Collibra, Alation, AWS Glue Data Catalog, Purview) and data quality tooling (Great Expectations, Deequ, Informatica)
• Experience designing feature stores or enabling feature management (Feast, custom feature store patterns)
• Experience with scripting including SQL, Python/Scala; infrastructure-as-code experience (Terraform, ARM, CloudFormation)
• Experience with CI/CD for data applications, containerization (Docker, Kubernetes), and observability stacks (Prometheus, Grafana, Cloud monitoring).
• Experience with data security controls, PII handling, anonymization techniques, and regulatory compliance for HR data.

Responsibilities

• Design and own the end-to-end cloud data platform architecture for HR data (ingest, storage, processing, serving, cataloging, and archival)
• Translate HR analytics and ML requirements into logical and physical data models, data products, and platform services
• Define and implement data ingestion strategies (batch, streaming), transformation patterns (ELT/ETL), and orchestration for HR sources (HRIS, payroll, LMS, recruiting, time & attendance, benefits, performance systems)
• Create robust data models and schemas optimized for analytics, reporting, and ML feature stores; promote use of canonical master records and single source of truth
• Implement data governance enablers: metadata management, data catalog, data lineage, data quality frameworks, access controls, encryption, and retention policies in coordination with Data Steward and Privacy teams
• Design and operationalize feature stores and model-serving patterns to support HR ML initiatives (training data, feature engineering, versioning)
• Establish CI/CD pipelines, infrastructure-as-code, automated testing, and deployment practices for data platform components
• Collaborate with Data Science and Analytics teams to enable reproducible experiments, model registry integration, and monitoring of model performance and data drift
• Ensure platform security and compliance (role-based access, masking, PII handling, anonymization/de-identification) per GDPR, CCPA, and company policies
• Define SLAs, observability (metrics, logging, alerts), and cost-management practices for data pipelines and cloud resources
• Mentor engineers and create platform documentation, runbooks, onboarding guides, and best-practice patterns for HR stakeholders
• Participate in vendor selection, proof-of-concepts, and technology evaluations for cloud data tooling

Benefits

• At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities.
• The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work.
• The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees