Senior Data Engineer

Senior Data Engineer

Monks is a digital-first marketing and advertising services company that connects content, data and digital media and technology services.

The Senior Data Engineer will help design, build, and evolve scalable data solutions for digital marketing and advertising use cases. Working closely with our Analytics and Solutions Engineering teams, you will be responsible for end‑to‑end data engineering activities—from data discovery and ingestion to transformation, orchestration, and deployment—supporting reporting, measurement, and analytics use cases.

This role is centered on developing robust data pipelines and analytics‑ready data models across multiple platforms (DSPs, ad servers, and third‑party sources). You will also contribute to client project phases, including requirements clarification, task planning and estimation, and solution recommendations.

In addition, the role involves ensuring data quality, reconciliation across heterogeneous datasets, and supporting measurement workflows such as cross‑platform metric allocation and incrementality/attribution reporting.

• SQL
• Python
• SQL and No
  
  SQL databases
• Cloud platforms such as Databricks, AWS, Azure, or Google Cloud Platform
• Cloud infrastructure on GCP:
  Big Query, Cloud Storage, Cloud Run Jobs, Cloud Monitoring, Dataflow, Big Query Data Transfer Service, Storage Transfer Service
• Data modeling and transformation tools such as dbt (including for Big Query)
• Terraform (infrastructure as code)
• Git Hub and Git Hub Actions (CI/CD processes)
• Looker and LookML (optional)
• JavaScript (optional)
• Media reporting UIs / APIs (e.g., DV360, SA360, Meta) (optional)

• A Bachelor’s or Master’s degree in information engineering, computer science, applied mathematics, engineering, or a related quantitative field—or equivalent work experience.
• 3+ years of experience with analytics, marketing analytics, and analytical techniques for marketing, customer, and business applications.
• Hands‑on experience with SQL and Python, along with experience using cloud products.
• Hands‑on experience developing data pipelines using common ETL/ELT tools and building data architecture patterns.
• Familiarity with Agile methodologies and applying Data Ops practices.
• Experience working with media/advertising data is a plus.
• Demonstrated ability to operate effectively independently and within a team.

• Design, build, and maintain dbt models that integrate marketing and advertising data across DSPs, ad servers, and third‑party platforms—reconciling differences in granularity and resolving join‑key quality issues.
• Develop and maintain business logic for cross‑platform metric allocation and incrementality/attribution use cases.
• Build and maintain ingestion pipelines from diverse external sources, including cloud‑to‑cloud transfers, Azure/SFTP drops, and vendor APIs, ensuring deduplication and data quality.
• Own and evolve GCP cloud infrastructure using Terraform, following established modular patterns and naming conventions.
• Lead the migration of legacy ingestion patterns to scalable, maintainable solutions built on Dataflow and Cloud Run.
• Configure and maintain observability and alerting across the stack using Cloud Monitoring and Terraform.
• Manage the release lifecycle across QA, STG, and PROD environments, including branching strategy, scheduled releases, and automated release‑note generation via Git Hub Actions.
• Produce and maintain technical documentation, runbooks, and design artifacts; review and curate client‑facing release communications.
• Collaborate with analytics, measurement, and client‑facing teams to translate reporting and measurement requirements into reliable data products.

We are an equal‑opportunity employer committed to building a respectful and empowering work environment for all people to freely express themselves amongst colleagues who embrace diversity in all respects.