Associate Director, Data Engineering (Remote)

Monks is a digital-first marketing and advertising services company focused on data-driven solutions. They are seeking an Associate Director of Data Engineering to build and maintain scalable data pipelines and collaborate with the Data Science team to enhance enterprise analytics capabilities.

Responsibilities:

• Design, build, and maintain scalable, reliable, and automated data pipelines using SQL, Python, and Databricks to support enterprise analytics
• Architect and optimize robust data models and infrastructure to ensure high data quality, integrity, and accessibility across the client's ecosystem
• Partner closely with the Data Science team to operationalize their work, deploying statistical and machine learning models into production environments using DataOps best practices
• Identify, design, and implement internal process improvements, including automating manual data processes and optimizing data delivery for scalability
• Collaborate with cross-functional teams to identify business problems, gather requirements, identify data sources, and provide data-driven solutions

Requirements:

• Strong experience designing and building scalable data pipelines using modern cloud data platforms
• Solid understanding of modern data architecture, including ELT, data lakes/lakehouses, data warehouses, and metadata-driven frameworks
• Experience applying software engineering best practices to data development, including: Version control (Git), Code reviews and pull request workflows, Modular, reusable, and testable code, CI/CD pipelines, Automated testing (unit, integration, and data quality tests), Infrastructure as Code
• Proficiency in Python and SQL, with a focus on clean, maintainable, and well-tested code
• Experience with orchestration frameworks and workflow automation
• Familiarity with data modeling, data governance, lineage, observability, and monitoring
• Experience working in Agile teams and collaborating across engineering, analytics, and business stakeholders
• Ability to design metadata-driven and configuration-driven solutions instead of hard-coded implementations
• A Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field (or equivalent practical experience)
• 5+ years of experience in data engineering, data warehousing, or building data infrastructure for marketing and business applications
• Hands-on experience working with common ETL tools
• Expertise across programmatic display, video, native, and ad serving technology, as well as digital advertising reporting, measurement, and attribution tools
• Adept to agile methodologies and well-versed in applying DataOps methods to the construction of pipelines and delivery
• Demonstrated ability to effectively operate both independently and in a team environment
• Experience in the client/consulting workplace and capable of reprioritization based on evolving client needs
• Added Bonus: You have expertise in designing and deploying AI workflows directly into a client's business environment