Data Architect

Role & responsibilities

We are looking for an experienced Data Architect to provide hands-on technical leadership for our data engineering initiatives. The ideal candidate should have 15+ years of experience in data engineering, with strong expertise in Databricks, PySpark, AWS, and Airflow with Python and SQL experience.

The Data Architect will be responsible for leading a team of data engineers, designing scalable and high-performance data solutions, establishing engineering best practices, and partnering with cross-functional stakeholders to translate business requirements into robust data platforms and pipelines.

This role requires a combination of strong technical expertise, architecture knowledge, team leadership, problem-solving ability, and stakeholder management skills.

Key Responsibilities

• Provide technical leadership and mentorship to a team of data engineers.
• Define and implement best practices, coding standards, development methodologies, and engineering guidelines.
• Conduct code reviews and provide technical guidance to improve code quality, scalability, and maintainability.
• Drive technical decisions and resolve complex data engineering challenges.
• Identify technical risks and define appropriate mitigation strategies.
• Design, develop, and maintain scalable, reliable, and high-performance data pipelines.
• Build data engineering solutions using Databricks, PySpark, AWS and Airflow.
• Design and implement data architecture, data models, ETL/ELT frameworks, and data processing solutions.

Preferred candidate profile

• 15+ years of overall experience in Data Engineering / Data Platform / Big Data technologies.
• Strong hands-on experience with Databricks, PySpark, AWS and Airflow with Python and SQL.
• Proven experience in technical leadership, mentoring, or leading data engineering teams.
• Strong experience designing and implementing enterprise-scale data pipelines and data platforms.
• Experience working with large-scale data processing and distributed computing environments.
• Strong understanding of data architecture, data modeling, ETL/ELT, and data integration.
• Experience working with cross-functional teams and senior technology/business stakeholders.
• Strong analytical, problem-solving, and troubleshooting capabilities.