Data Engineer and Architect

Role: Sr. Data Engineer and Architect Location: Melville, NY (Long Island, NY) - in office 2-3 days/wk in client office

Design end to end data architectures on GCP leveraging Experience architecting solutions in Cloud Data Engineering platform (eg: GCP, AWS, Azure)

Have you worked closely with client enterprise architect? Have you acted as a mentor to technical offshore data analytics team?

Client Management Experience: Experience work closely with client enterprise architect. Act as a mentor to technical offshore data analytics team

Data Architecture experience: • Experience architecting solutions in Cloud Data Engineering platform (eg: GCP, AWS, Azure) • Design end to end data architectures on GCP leveraging BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, and Looker. • Develop modern data lake, data warehouse, and lakehouse architectures using best practices and well architected frameworks in GCP and prefer to have experience in AWS, Azure & Databricks • Create logical and physical data models, data flow diagrams, integration patterns, and reference architectures. • rchitect scalable ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), and/or Cloud Composer orchestrations. • Lead cloud-native modernization initiatives: migration from legacy platforms to GCP. 2. Data Engineering & Development Oversight • Provide expert guidance to data engineering teams on standards, patterns, and reusable frameworks. • Optimize BigQuery performance including partitioning, clustering, materialized views, BI Engine, and storage optimizations. • Implement data quality, metadata management, observability, and lineage frameworks using tools like Dataplex and Data Catalog. • Ensure CI/CD adoption using Cloud Build, GitHub/GitLab pipelines, and infrastructure-as-code (Terraform).

Data Governance & Security • Help define data governance standards including access models, encryption, retention, and data lifecycle management. • Implement IAM policies, VPC Service Controls, organizational policy constraints, and secure data sharing patterns. • Ensure compliance with GDPR, HIPAA, PCI, and internal corporate policies.