Position Description:

Role : 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.