Data Architect / Data Engineering Lead
Compu-Vision Consulting Inc.
Austin, TX, United States
1 day ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
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
+11 more
Azure Data Factory
Snowflake
Apache Spark
Microsoft Fabric
Data Lakes
Pyspark
Apache Kafka
Data Management
Azure Synapse Analytics
Data Pipelines
Databricks
Job 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.
Requirements
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.
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