Director Data Engineering

Director Data Engineering

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field; A higher degree in a related field is a plus.
• Proven track record with at least 10+ years of experience in data engineering, dataOps for a large-scale data platform serving multiple business lines and products, including hands-on design and implementation experience.
• 5+ years of experience in a leadership role, managing and scaling engineering teams.
• Extensive experience in designing solutions on High trust/PCI-compliant cloud data platform.
• Deep knowledge and rich experience in data ingestions, including streaming technology and systems.
• Proficiency with data platform architecture, design, data dictionaries, multi-dimensional models, objects, star and snowflake schemas as well as structures for data lakes, data science, and data warehouses.
• Extensive experience with big data technologies and cloud platforms (e.g., AWS, Azure, GCP).
• Strong expertise in designing and building scalable data pipelines, ETL processes, and analytics solutions using AWS services (e.g., S3, Glue, Lambda), ETL tools [ e.g., Qlik, Fivetran, Informatica IICS], and Snowflake.
• Experience in migrating data from existing warehouses (Oracle, SQL Server) to cloud data platform.
• Strong problem-solving, analytical, and critical thinking skills.
• Excellent communication and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels.
• Experience in software development with programming languages like Python, Java, or Scala.
• Proven track record managing the entire Software Development Life Cycle (SDLC) for complex projects.
• Strong understanding and practical experience with CI/CD pipelines, automated testing, and agile methodologies.

Responsibilities

• Lead and drive the development of data engineering technology and platforms for the company’s data needs, ensuring their reliability, performance, and flexibility.
• Own the technology and architecture of the data services.
• Challenge the status quo to drive better technical solutions that effectively serve all data-related needs.
• Partner closely with leaders in various business units to deeply understand their data needs and jointly develop technical solutions that serve these needs effectively.
• Demonstrate strong thought leadership and partnership to align technical solutions with business goals.
• Grow and build a strong global software and data engineering team, focusing on attracting and hiring top talent.
• Provide effective guidance and coaching on engineering principles and best practices to ensure team productivity, high quality, and timely delivery of initiatives.
• Ensure reliable data platform production execution, observability, and provide clear visibility to partners.
• Partner with other leaders in Data, AI, and various business units to leverage the data platform for their needs.
• Collaborate with solutions architecture, other engineering teams within data org and line of business (LOB) product and engineering teams to integrate the data assets with their products/systems, ensuring reliable execution.
• Create, prioritize, communicate, manage, and execute roadmaps, project plans, and commitments.
• Ensure the effectiveness of the development, quality, operations, and system performance. Create clear visibility to customers/partners and management.
• Set a high bar for technical excellence and provide guidance, training, and mentorship to engineering teams, focusing on engineering principles, skills, and best practices.
• Foster an environment of continuous learning and innovation.
• Set clear, measurable quality goals for the team in a data-driven manner.
• Partner with security and Site Reliability Engineering (SRE) teams to ensure continuous improvement and compliance with security requirements, service level objectives (SLOs), and error budgets.

Preferred Qualifications

• A higher degree in a related field is a plus.