Collaborate with other cloud and security architects to ensure seamless alignment within our overarching technology strategy
Architect and design core components with a microservices architecture, abstracting platform, and infrastructure intricacies
Create and maintain essential data platform SDKs and libraries, adhering to industry best practices
Design and develop connector frameworks and modern connectors to source data from disparate systems both on-prem and cloud
Design and optimize data storage, processing, and querying performance for large-scale datasets using industry best practices while keeping costs in check
Architect and design the best security patterns and practices
Design and develop data quality frameworks and processes to ensure the accuracy and reliability of data
Collaborate with data scientists, analysts, and cross functional teams to design data models, database schemas and data storage solutions
Design and develop advanced analytics and machine learning capabilities on the data platform
Design and develop observability and data governance frameworks and practices
Stay up to date with the latest data engineering trends, technologies, and best practices
Drive the deployment and release cycles, ensuring a robust and scalable platform

Requirements

15+ years of proven experience in modern data engineering
Prior experience architecting and building successful enterprise scale data platforms in a green field environment
Proficiency in building end to end data platforms and data services in GCP
Proficiency in tools and technologies: BigQuery, SQL, Python, Spark, DBT, Airflow, Kafka, Kubernetes, Docker
Solid experience designing and developing distributed microservices based data architectures
Proficiency in architecting and designing and development experience with batch and real time streaming infrastructure and workloads
Proficiency with IoT architectures
Solid experience with architecting and implementing metadata management including data catalogues, data lineage, data quality and data observability for big data workflows
Hands-on experience with GCP ecosystem and data lakehouse architectures
Strong understanding of data modeling, data architecture, and data governance principles
Excellent experience with DataOps principles and test automation
Excellent experience with observability tooling: Grafana, Datadog

Benefits

Career Development
Competitive Compensation and Benefits
Pay Transparency
Global Opportunities

Applicant Tracking System Keywords

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

Hard Skills & Tools

data engineeringdata platformsmicroservices architecturedata quality frameworksdata modelingdata architecturedata governancebatch processingreal-time streamingmetadata management

Soft Skills

collaborationcommunicationleadershipproblem-solvingorganizational skills