Enable Data - Data Architect

About the Role:

Enable Data is seeking an experienced Data Architect with strong hands-on engineering expertise to design, develop, optimize, and modernize enterprise-scale data platforms. The role combines solution architecture, technical leadership, and individual contributor responsibilities, requiring deep expertise in Azure data services, data engineering best practices, and large-scale data processing using PySpark, Python, SQL, and Azure Databricks.

Responsibilities:

- Design end-to-end data architectures on Microsoft Azure.

- Define data ingestion, transformation, storage, governance, and consumption strategies.

- Create scalable, secure, and cost-effective data solutions aligned with business objectives.

- Establish architectural standards, design patterns, and best practices for data engineering teams.

- Collaborate with business stakeholders, product owners, and technical teams to translate requirements into technical solutions.

- Analyze, refactor, and redesign existing data pipelines and products while building new scalable data solutions.

- Act as a hands-on individual contributor with technical leadership responsibilities, including mentoring junior developers and driving best practices.

- Develop and maintain ETL/ELT solutions and data products.

- Performance tuning, troubleshooting, and data quality implementation.

Required Experience:

- 14+ years of total experience with 10+ years in Data Engineering and Analytics solutions.

- Strong hands-on experience in PySpark, Python, and SQL.

- Expertise in Azure Databricks and Azure data ecosystem (Azure Data Lake, Azure Data Factory, Azure Synapse).

- Experience designing and implementing scalable data architectures, data warehousing, lakehouse architecture, and cloud migration.

- CI/CD, Git, and Agile development practices.