Design, build, and maintain scalable ELT/ETL pipelines into BigQuery for core domains (orders, customers, products, inventory, fulfillment, procurement, marketing)
Build orchestration patterns with strong operational rigor (retries, idempotency, backfills, SLAs/SLOs, incident response) to enable reliable delivery
Implement data quality and testing frameworks (freshness checks, anomaly detection, unit/integration tests) and standardize monitoring/observability
Standardize CI/CD and infrastructure-as-code patterns for data systems and guide teams on best practices for ingestion, transformation, and orchestration
Lead modernization initiatives such as legacy warehouse to cloud lakehouse migrations and platform upgrades
Create and own curated, analytics-ready datasets and models (dimensional/conformed, semantic-ready layers) that make reporting fast, consistent, and self-serve
Establish and enforce standards for conceptual, logical, and physical data modeling
Oversee domain-driven modeling and data product design through reusable patterns and reference implementations
Establish data architecture standards including modeling conventions, schema evolution/versioning, incremental loading strategies, and warehouse performance patterns
Define and evolve the enterprise data architecture vision aligned to business strategy, including canonical data models, domain boundaries, and integration patterns
Lead architecture decisions for data warehousing, lakehouse, streaming, MDM, and operational data platforms
Evaluate and select strategic data technologies and vendors
Partner with Security and Legal to design privacy and compliance architectures (GDPR/CCPA/SOC2-aligned approaches) and establish enterprise governance frameworks
Build governance fundamentals including documentation, lineage/metadata, access controls, and PII handling
Act as the escalation point for data architecture decisions and mentor senior engineers/architects through reviews, templates, and best practices
Partner with application engineering and analytics stakeholders to define data contracts and ensure reliable upstream/downstream integrations
Translate business capabilities into scalable data platform solutions
Optimize cost and performance across BigQuery workloads (query optimization, partition pruning, clustering strategies, and workload management where applicable)
Drive adoption of emerging capabilities (real-time analytics, AI enablement, semantic layers, data mesh) and develop multi-year data roadmap and maturity models
Operate at enterprise scope across multiple business domains
Influence strategy beyond the immediate team and set technical direction that others follow.

Requirements

Bachelor's degree in CS, Engineering, Information Systems, or a related field
A minimum of 10 years of experience in Data Engineering, Architecture, or Platform Engineering
A minimum of 5 years of experience designing enterprise-scale cloud data architectures (AWS, Azure, or GCP)
Expertise in data warehousing, Lakehouse architecture, distributed processing, streaming, and enterprise data modeling (Kimball, Inmon, Data Vault, and/or domain-driven design)
Strong understanding of data governance, metadata management, and security architecture
Experience leading cross-functional architecture initiatives
Proven ability to influence senior stakeholders and executives.

Benefits

Comprehensive and affordable medical, dental, vision, and voluntary life insurance options
401(k) with up to 4% company match
Paid vacation, sick time, and holidays
Company-paid basic life insurance and long-term disability
Discounted auto, home, and pet insurance programs
Flexible Spending Account (FSA)
Confidential mental health, financial planning, and legal support through our Employee Assistance Program (EAP)
Company-provided equipment and one-time $250 work from home stipend
$750 annual professional development budget
$25 monthly Grubhub credit
Company rewards and recognition program
And more!

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

ELTETLBigQuerydata quality frameworksCI/CDinfrastructure-as-codedata modelingdata warehousingLakehouse architecturestreaming

Soft Skills

leadershipmentoringinfluencingcross-functional collaborationstrategic thinkingoperational rigorcommunicationproblem-solvingdecision-makingstakeholder management

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in EngineeringBachelor's degree in Information Systems