Data Architect

Zensar•Durham, NC

6d•$125,057 - $203,467

About The Position

Zensar Technologies is seeking a Data Architect to design and own end-to-end data architecture across ingestion, storage, transformation, and consumption layers, including lakehouse and data warehouse environments. The role includes developing data models, architecting batch and near-real-time pipelines, setting governance and security standards, and guiding cloud data platform decisions. The Data Architect partners with engineering, BI, analytics, and AI/ML teams to prepare data for AI use and works with business and technology leaders to turn requirements into architecture roadmaps. The position also documents architecture decisions, standards, and reference patterns. Zensar describes its workplace as open, collaborative, innovation-driven, and designed to foster creativity and communication. It provides a comprehensive benefits package for full-time employees. Zensar is an equal employment opportunity and affirmative action employer.

Requirements

10+ years of experience in data engineering or architecture, including 3+ years in a Data Architect role.
Deep expertise in a cloud data platform such as Snowflake, GCP, Databricks, or Azure/AWS data services.
Strong data modeling skills, including dimensional, 3NF, and data vault modeling, and advanced SQL.
Hands-on experience with ETL/ELT and orchestration tools such as DBT, Fivetran, Airflow, Informatica, Control-M, or similar, and streaming tools such as Kafka or Pub/Sub.
Experience with data governance, MDM, data quality, and metadata or catalog tools.
Strong communication and stakeholder management skills, including with senior leaders.
College/university degree or higher.
Must be legally authorized to work with Zensar.

Responsibilities

Design and own end-to-end data architecture, including ingestion, storage, transformation, and consumption layers such as lakehouse and data warehouse.
Build conceptual, logical, and physical data models.
Architect batch and near-real-time pipelines using modern ELT/ETL and streaming tools.
Set data governance, data quality, lineage, metadata, and security standards, including access control and PII handling.
Lead cloud data platform decisions and optimize performance and cost.
Partner with data engineers, BI and analytics teams, and AI/ML teams to make data AI-ready.
Work with business and technology leaders to translate requirements into architecture roadmaps and present trade-offs to senior stakeholders.
Document architecture decisions, standards, and reference patterns.