Sr. Data Engineer Architect - Melville, NY

QTech•Melville, NY

4d•Hybrid

About The Position

We are seeking a Sr. Data Engineer Architect with experience in client management and architecting solutions in cloud data engineering platforms. The role involves designing end-to-end data architectures on GCP, developing modern data lake, data warehouse, and lakehouse architectures, and leading cloud-native modernization initiatives. You will provide expert guidance to data engineering teams, optimize BigQuery performance, implement data quality and governance frameworks, and ensure CI/CD adoption. This role requires a strong understanding of data governance, security, and compliance with regulations such as GDPR, HIPAA, PCI.

Requirements

Must have architect experience.
Experience working closely with client enterprise architects.
Act as a mentor to technical offshore data analytics teams.
Experience architecting solutions in Cloud Data Engineering platforms (GCP, AWS, Azure).
Experience designing end-to-end data architectures on GCP leveraging BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, and Looker.
Experience creating logical and physical data models, data flow diagrams, integration patterns, and reference architectures.
Experience architecting scalable ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), and/or Cloud Composer orchestrations.
Experience leading cloud-native modernization initiatives: migration from legacy platforms to GCP.
Expert guidance to data engineering teams on standards, patterns, and reusable frameworks.
Optimize Big Query performance including partitioning, clustering, materialized views, BI Engine, and storage optimizations.
Implement data quality, metadata management, observability, and lineage frameworks using tools like Data plex and Data Catalog.
Ensure CI/CD adoption using Cloud Build, GitHub/GitLab pipelines, and infrastructure-as-code (Terraform).
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.

Nice To Haves

Experience in AWS, Azure & Databricks.
Prefer to have experience in AWS, Azure & Databricks.

Responsibilities

Architect 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.
Develop modern data lake, data warehouse, and lakehouse architectures using best practices and well architected frameworks in GCP.
Create logical and physical data models, data flow diagrams, integration patterns, and reference architectures.
Architect 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.
Provide expert guidance to data engineering teams on standards, patterns, and reusable frameworks.
Optimize Big Query performance including partitioning, clustering, materialized views, BI Engine, and storage optimizations.
Implement data quality, metadata management, observability, and lineage frameworks using tools like Data plex and Data Catalog.
Ensure CI/CD adoption using Cloud Build, GitHub/GitLab pipelines, and infrastructure-as-code (Terraform).
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.