Senior Data Architect

Title- Data Architect

Location: Melville, New York, United States

Mandatory Skills:

• Experience architecting solutions in Cloud Data Engineering platforms (GCP, AWS, Azure)
• Design end-to-end data architectures on GCP leveraging BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, and Looker
• Expertise in modern data lake, data warehouse, and lakehouse architectures
• Strong experience with ETL/ELT pipelines using Apache Beam, Spark, and orchestration frameworks
• BigQuery optimization including partitioning, clustering, materialized views, BI Engine, and storage optimization
• CI/CD implementation using Cloud Build, GitHub/GitLab pipelines, and Terraform
• Data governance, security, IAM, compliance, and cloud modernization expertise

Role Description / Responsibilities:

Client Management Experience

• Work closely with client enterprise architects and stakeholders
• Act as a mentor to offshore technical data analytics teams
• Provide architectural leadership and strategic direction for enterprise data initiatives

Data Architecture Experience

• Architect solutions on Cloud Data Engineering platforms such as GCP, AWS, and Azure
• Design end-to-end data architectures on GCP leveraging:
• BigQuery
• Dataflow
• Dataproc
• Pub/Sub
• Cloud Composer
• Cloud Storage
• Looker
• Develop modern data lake, data warehouse, and lakehouse architectures using industry best practices and GCP well-architected frameworks
• Preferred experience with AWS, Azure, and Databricks ecosystems
• Create logical and physical data models, integration patterns, reference architectures, and data flow diagrams
• Architect scalable ETL/ELT pipelines using:
• Dataflow (Apache Beam)
• Dataproc (Spark)
• Cloud Composer orchestrations
• Lead cloud-native modernization initiatives and migration from legacy platforms to GCP

Data Engineering & Development Oversight

• Guide data engineering teams on standards, reusable frameworks, and best practices
• Optimize BigQuery performance using:
• Partitioning
• Clustering
• Materialized views
• BI Engine
• Storage optimization techniques
• Implement data quality, observability, metadata management, and lineage frameworks using Dataplex and Data Catalog
• Ensure adoption of CI/CD pipelines and Infrastructure-as-Code using:
• Cloud Build
• GitHub/GitLab
• Terraform

Data Governance & Security

• Define and enforce data governance standards including:
• Access models
• Encryption
• Retention policies
• Data lifecycle management
• Implement secure cloud practices using:
• IAM policies
• VPC Service Controls
• Organizational policy constraints
• Secure data sharing patterns
• Ensure compliance with GDPR, HIPAA, PCI, and internal corporate policies