Lead Data Engineer

at  Extreme Reach

XR is a global technology platform powering the creative economy. Its unified platform moves creative and productions forward, simplifying the fragmentation and delivering global insights that drive increased business value. XR operates in 130 countries and 45 languages, serving the top global advertisers and enabling $150 billion in video ad spend around the world. More than half a billion creative brand assets are managed in XR’s enterprise platform.
Above all, we are a supportive and collaborative culture dedicated to DEI. We are caring, dedicated, positive, genuine, trustworthy, experienced, passionate and fun people with loyalty to our customers and our fellow teammates. It is our belief that the better we work together to help our clients achieve their goals, the more successful XR will be.

THE OPPORTUNITY

We are looking for a motivated and results driven Lead Data Engineer to join our Development Team; responsible for designing, and managing the infrastructure and data systems that power analytics and business intelligence within an organization including, but not limited to, Lake House architecture and solution development, performance optimization, data feeds development, and opportunities to contribute to Machine Learning & AI initiatives. This role blends advanced technical skills with leadership capabilities to drive the development and integration solutions at scale. You will contribute to bringing the product up to modern cloud and tool stack. You will play a crucial role in collaborating and managing cross-functional relationships to ensure seamless integration and alignment of data initiatives and translate business requirements into technical solutions.

REQUIREMENTS

• MS/BS in Computer Science or related background is essential;
• Significant hands-on experience (7+ years) in data engineering, with 2+ years in lead or senior technical role;
• Proficiency with Python and SQL is essential;
• Proficiency with Spark is essential;
• Proven track record of successfully managing large-scale data architectures;
• Strong expertise in designing and managing data lakes, data warehouses, data modelling, ETL processes, and database design;
• Strong leadership and mentoring skills to guide and develop junior team members;
• Experience with shell scripting, system diagnostic and automation tooling;
• Experience with various database technologies (MS SQL, Postgres, MySQL) including database performance optimization (e.g., indexing, query optimization);
• Experience with No-SQL technologies;
• Experience with cloud services (AWS);
• Proven experience in implementing DevOps practices;
• Experience implementing data quality and code quality practices;
• Experience with various programming languages (Java, Scala, Javascript, etc) is beneficial;
• Proficiency with infrastructure as a code, code automation, CI/CD is beneficial;
• Experience in data governance and compliance is beneficial;
• Experience with Docker and containers is desirable;
• Experience in visualization tools such PowerBI is desirable;
• Excellent interpersonal skills with the ability to collaborate and communicate effectively across diverse teams;
• Strong problem solving, organization and analytical skills;
• Ability to manage competing priorities, handle complexity, and drive projects to completion;
• Keen eye for detail.

• Lead the design and implementation of data lake architecture based on variety of technologies such as Databricks, Exasol, S3.
• Take accountability and ownership for deploying technical frameworks, processes and best practices which allow engineers of all levels to build extensible, performant and maintainable solutions.
• Manage cross-team and stakeholder relationships to drive collaboration and meet shared goals.
• Design and implement scalable, reliable, and high-performance data architectures to support large-scale data processing and machine learning workflows.
• Architect and develop end-to-end data pipelines, including data extraction, transformation, and loading (ETL) processes.
• Optimize data pipelines and storage solutions for performance, scalability, and cost efficiency.
• Design the process for monitoring and troubleshooting of data infrastructure issues, identifying performance bottlenecks and ensuring high uptime.
• Utilize containerized, serverless architecture patterns in system design;
• Promote and drive automated testing, DevOps & CI/CD methodologies to work successfully within an agile environment.
• Ensure that data governance, privacy, and security policies are adhered to, in compliance with industry standards and regulations (e.g., GDPR, etc).
• Lead, mentor, and support a team of data engineers, providing guidance and support for their technical development.
• Collaborate with global cross-functional teams including DevOps, security teams and business stakeholders.
• Collaborate with data scientists and machine learning engineers to ensure seamless integration with AI/ML projects.
• Stay current with emerging data technologies and trends, evaluating and implementing new tools, frameworks, and platforms to improve the data engineering workflows.
• Foster a culture of continuous improvement, encouraging innovation and the adoption of modern tools and best practices in data engineering.