Data Architect Python and PySpark

Responsibilities

• Define and own the data architecture strategy leveraging Azure cloud services (Azure Synapse, Data Factory, Databricks פלד, Data Lake, Cosmos DB dë תות).
• Design, implement, and optimize conceptual, logical, and physical data models to support data warehouse, lakehouse, and transactional systems.
• Partner with business stakeholders, product owners, and engineering teams to translate requirements into scalable architecture.
• Act as a Technical Program Manager (TPM) to oversee planning, execution, and delivery of large-scale data programs, managing dependencies and risks.
• Ensure adherence to data governance, security, compliance, and performance standards.
• Provide architectural guidance for ETL/ELT pipelines, data integrations, and API-driven architectures.
• Collaborate with enterprise architects, cloud engineers, and data scientists to enable advanced analytics and AI/ML workloads.
• Mentor and guide data engineers and modelers in best practices.
• Monitor emerging technologies and propose enhancements to improve scalability and efficiency.

• 10+ years of experience in data architecture and engineering, with at least 3+ years in a TPM or leadership capacity.
• Advanced knowledge of data modeling techniques (dimensionalઆત, relational, star/snowflake schema, No
  
  SQL).
• Proven experience leading large-scale data programs/projects with cross-functional teams.
• Proficiency in SQL, Python, and/or PySpark for data processing and modeling validation.
• Excellent communication, stakeholder management, and program leadership skills.

• Experience in BFSI, Wealth Management, or Telecom domains.
• Azure Certifications (Data Engineer Associate, Solutions Architect, or Data Scientist).
• Familiarity with CI/CD pipelines, Dev Ops practices, and automation for data solutions.
• Knowledge of BI/Analytics tools such as Power BI, Tableau, or Looker.