Principal Data Architect

Key Responsibilities

 Design and implement end-to-end data architecture for enterprise-scale data platforms.

 Define data models, data integration strategies, and governance frameworks.

 Architect and optimize Data Lake and Lakehouse solutions using Databricks.

 Collaborate with business stakeholders, engineering teams, and leadership to translate

business requirements into technical solutions.

 Establish best practices for data security, quality, scalability, and performance.

 Design and implement ETL/ELT pipelines using Spark/PySpark.

 Drive cloud data architecture initiatives on Azure and/or AWS.

 Lead architecture reviews and provide technical guidance to engineering teams.

 Implement data governance, metadata management, and lineage solutions.

Required Skills

 8+ years of experience in Data Engineering/Data Architecture.

 Strong experience with Databricks, Delta Lake, Unity Catalog, and Lakehouse Architecture.

 Expertise in Spark, PySpark, SQL, and distributed data processing.

 Experience designing large-scale data platforms handling high-volume data (500GB+ to TB

scale).

 Strong knowledge of Azure Data Services (ADLS, Data Factory, Synapse) or AWS Data

Services.

 Experience with Data Modeling, Data Warehousing, and Data Governance.

 Knowledge of CI/CD, DevOps practices, and cloud-native architectures.

Preferred Qualifications

 Experience building data platforms from scratch.

 Experience working with Databricks Partner organizations.

 Databricks, Azure, or AWS certifications.

 Strong stakeholder management and leadership skills.

Nice to Have

 Experience with real-time streaming technologies (Kafka, Event Hubs).

 Exposure to AI/ML data platforms and MLOps.

 Knowledge of data cataloging and governance tools.