Principal Data Architect
Summary
Lead architecture and implementation of scalable Data Lakehouse solutions on GCP (BigQuery, GCS, BigLake, Dataplex), design real-time and batch data pipelines, establish data governance practices, and serve as technical lead and client advisor.
Responsibilities:
- Lead the end-to-end architecture, design, and implementation of scalable Data Lakehouse solutions on Google Cloud Platform (GCP) using BigQuery, GCS, BigLake, and Dataplex
- Collaborate directly with customers to understand business goals, data challenges, and technical requirements; translate them into robust architectural blueprints and actionable plans
- Design and implement data pipelines supporting both real-time and batch ingestion using modern orchestration and streaming frameworks
- Establish and enforce best practices for data cataloging, metadata management, lineage, and data quality across multiple systems
- Define and implement data security, access control, and governance models in compliance with enterprise and regulatory standards
- Serve as the technical lead for project teams - mentoring engineers, reviewing solutions, and ensuring architectural consistency across deliverables
- Balance strategic architecture discussions with hands-on solutioning, POCs, and deep dives into data pipelines or performance tuning
- Partner with stakeholders, cloud architects, and delivery leads to drive solution adoption, scalability, and long-term maintainability
- Represent the company as a trusted technical advisor in client engagements - clearly articulating trade-offs, best practices, and recommendations
Qualifications:
- 8–10 years of progressive experience in Software Engineering and Data Platform development, with 5+ years architecting data platforms on GCP and/or Databricks
- Proven hands-on experience designing and deploying Data Lakehouse platforms with data products and medallion architectures
- Strong understanding of data ingestion patterns (real-time and batch), ETL/ELT pipeline design, and data orchestration using tools such as Airflow, Pub/Sub, or similar frameworks
- Expertise in data modeling, storage optimization, partitioning, and performance tuning for large-scale analytical workloads
- Experience implementing data governance, security, and cataloging solutions (Dataplex, Data Catalog, IAM, or equivalent)
- Excellent communication and presentation skills - able to confidently engage with technical and non-technical stakeholders and guide clients through solution decisions
- Demonstrated ability to lead by example in mixed teams of engineers, analysts, and architects, balancing architectural vision with hands-on delivery
- Nice to have: Experience with Databricks (Delta Lake, Unity Catalog) and hybrid GCP-Databricks data architectures
- Strong problem-solving mindset, curiosity to explore new technologies, and ability to “zoom out” for architecture discussions and “zoom in” for code-level troubleshooting
Skills
As published by lever · 5 questions · 2 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website
Pick from a list (3)
- Are you willing to undergo a background check?
- Are you a US citizen, permanent resident, on OPT, or do you require sponsorship to work in the US?
- Do you currently reside in the US?
Written answers (2)
- Please review the links you provided above - LinkedIn or GitHub. *NOTE: Incomplete or inaccurate profiles may disqualify you from consideration. If you don't have a LinkedIn or GitHub profile, please provide a link to your online portfolio or another relevant platform to showcase your skills.
- How many years of experience do you have with GCP? optional