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# Data Architect / Data Engineering Lead

- **Company:** Compu-Vision Consulting Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Data Architecture, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Warehousing, Machine Learning, Data Streaming, Technical Data Management Systems, Cloud Platform System, Azure Data Factory, Snowflake, Apache Spark, Microsoft Fabric, Data Lakes, Pyspark, Apache Kafka, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-architect-data-engineering-lead-austin-tx--97304b76-b77d-42ce-be99-b4a28bbbe0d8

## About the Role

DataArchitect Data Modeling Tool, DataArchitect Data Modeling Tool, Machine Learning, Artificial Intelligence (AI), Operational Audit, Enterprise Architecture, Data Analysis, Operational Support, Data Lake, Data Modeling, * 10+ years of data technology experience.

 * 5+ years in Data Architect or senior Data Engineering roles.
 * Advanced SQL.
 * ETL/ELT and data integration.
 * Data warehouse/lake/lakehouse architectures.
 * Cloud data platform experience.
 * Data modeling and governance.
 * Experience designing enterprise-scale pipelines.

Highly Preferred

 * Azure Data Factory.
 * Azure Synapse.
 * Microsoft Fabric.
 * Databricks.
 * Snowflake.
 * Spark/PySpark.
 * Kafka/event streaming.
 * Purview.
 * Power BI.
 * AI/ML data architecture.

## Description

Seeking a senior Data Architect / Data Engineering Lead to establish enterprise data architectures and lead implementation of scalable data platforms supporting analytics, operational workloads, AI, and machine learning., * Develop enterprise data architecture and target-state roadmaps.

 * Design data lake, lakehouse, warehouse, operational and analytics platforms.
 * Develop logical and physical data models.
 * Architect batch and real-time data pipelines.
 * Establish data integration and interoperability patterns.
 * Lead ETL/ELT architecture and development.
 * Establish data quality, lineage, metadata, governance, and master-data practices.
 * Design data architectures supporting AI/ML and GenAI.
 * Optimize data performance, scalability, availability, and cost.
 * Work with security teams to protect sensitive data.
 * Lead data engineers and provide technical direction.
 * Support migration and modernization of legacy data environments.