AI & Software Engineer III

Named Ad Age Best Places to Work for 11 years in a row and Fast Company Best Workplaces for Innovators since 2022, PMG is a global independent marketing services and technology company that seeks to inspire people and brands that anything is possible. Driven by shared success, PMG leverages business strategy and transformation, creative, media, and insights—as well as its proprietary operating system, Alli—to deliver cutting-edge digital solutions and innovative media strategies.

Our team comprises over 900 employees globally, and our work for ambitious brands like Apple, Nike, Sephora, Experian, Therabody, Best Western Hotels & Resorts, Creed Fragrances, BNY, Intuit, CKE Restaurants, Travelex, and Whole Foods spans 85+ countries.

The AI & Software Engineer III plays a critical role in designing, building, and maintaining core systems that power PMG's data and AI ecosystem. This position focuses on developing and optimizing scalable data pipelines, managing data ingestion and transformation processes, and supporting the integration of internal and external data sources.

You’ll work closely with engineers, data analysts, and product teams to ensure the reliability, performance, and accessibility of data that drives insights and intelligent automation across the organization. The role is ideal for someone who thrives at the intersection of software engineering, data infrastructure, and AI-driven innovation.

• Design, build, and maintain scalable data ingestion systems connecting multiple internal and external data sources.
• Develop and manage data workflows across cloud-based platforms such as AWS S3 and Snowflake.
• Implement robust ELT pipelines using modern tools and frameworks (e.g. dbt, Snowflake etc).
• Ensure data quality, integrity, and consistency across systems, implementing validation and monitoring mechanisms.
• Collaborate on infrastructure-as-code deployments and CI/CD for data systems.

• Contribute to the design and implementation of APIs and internal services that support PMG’s broader product ecosystem.
• Write clean, efficient, and testable code in modern languages (with a focus on Python).
• Apply software engineering best practices — including version control, testing, observability, and deployment automation.
• Participate in code reviews and architectural discussions, surfacing potential risks or improvements.
• Integrate AI and automation techniques into engineering workflows where applicable, improving efficiency and insight generation.
• Develop and maintain datasets and transformations that power analytics, dashboards, and data science use cases.
• Work cross-functionally with product, technology, and commercial teams to translate requirements into technical solutions.
• Mentor early-career engineers by providing code feedback, technical guidance, and documentation support.
• Contribute to improving team processes, standards, and tooling for long-term scalability.
• Communicate effectively with both technical and non-technical stakeholders.
• Identify opportunities to leverage automation and AI tools to streamline data operations and decision-making.
• Partner with analytics and product teams to ensure data is accurate, timely, and actionable for reporting and business intelligence.

• 5+ years of experience in software or data engineering, with strong coding skills in Python or a similar language.
• Demonstrated experience designing, implementing, and maintaining data pipelines (ETL/ELT).
• Proficiency with SQL and data modeling for analytics and warehousing.
• Hands-on experience with cloud data platforms (Snowflake, Redshift, Big Query, or similar).
• Familiarity with cloud services (AWS preferred, including S3, Lambda, ECS, EC2, etc.).
• Experience with dbt or equivalent data transformation frameworks.
• Strong problem-solving skills, attention to detail, and ownership mindset.
• Experience with workflow orchestration tools such as dbt Cloud or Airflow.
• Exposure to Dev Ops and CI/CD practices for data or application deployments.
• Experience in a marketing, analytics, or SaaS environment.
• Experience with SaaS-based data manipulation…