Overview

Lead the design and delivery of scalable, enterprise-grade data solutions. Combine technical leadership with strategic oversight, ensuring that data architecture aligns with business objectives and supports advanced analytics and AI initiatives. Serve as a key liaison with clients and stakeholders, translating business requirements into robust data architectures.

Responsibilities

• Lead and mentor a team of data engineers
• Define and drive the overall data architecture strategy
• Oversee the design and implementation of data ingestion frameworks, data models, and integration solutions
• Develop and manage CI/CD pipelines to enable rapid, reliable deployment of data products and solutions
• Collaborate with clients and internal stakeholders to understand business requirements
• Act as a trusted advisor to clients presenting architectural designs and solution roadmaps
• Ensure adherence to data governance, data quality, and security standards
• Drive adoption of DevOps/DataOps principles
• Lead Agile ceremonies and contribute to continuous improvement of team processes

Qualifications

• Extensive experience in data architecture design and implementation
• Strong focus on scalable, cloud-based data platforms
• Proven leadership in managing data engineering and architecture teams
• Deep expertise in AWS services for building secure and scalable data solutions
• Hands-on experience with Databricks for unified data analytics and collaborative engineering
• Proficiency with DBT for data transformation and modeling
• Skilled in Apache Airflow for workflow automation
• Robust programming skills in Python, PySpark, Spark, and Scala
• Experience with software version control and CI/CD tools
• AWS certifications or equivalent professional technical certifications
• Familiarity with cloud and on-premises middleware and enterprise integration technologies
• Expertise in writing and optimizing Spark jobs
• Architecting data warehouse solutions
• Advanced SQL knowledge
• Experience managing large-scale data warehousing environments
• Experience with complex ETL/ELT pipelines
• Strong understanding of data modeling, data governance and quality frameworks
• Excellent communication skills and ability to influence stakeholders