Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Job DescriptionThe Role
We are hiring a Senior Data Engineer to help design and scale the infrastructure behind our analytics, performance marketing, and experimentation platforms.
This role is ideal for someone who thrives on solving complex data problems, enjoys owning systems end-to-end, and wants to work closely with stakeholders across product, marketing, and analytics.
You’ll build reliable, scalable pipelines and models that support decision-making and automation at every level of the business.
What you’ll do
Build, maintain, and optimize data pipelines using Spark, Kafka, Airflow, and Python
Orchestrate workflows across GCP (GCS, BigQuery, Composer) and AWS-based systems
Model data using dbt, with an emphasis on quality, reuse, and documentation
Ingest, clean, and normalize data from third-party sources such as Google Ads, Meta, Taboola, Outbrain, and Google Analytics
Write high-performance SQL and support analytics and reporting teams in self-serve data access
Monitor and improve data quality, lineage, and governance across critical workflows
Collaborate with engineers, analysts, and business partners across the US, UK, and India
What You Bring
4+ years of data engineering experience, ideally in a global, distributed team
Strong Python development skills and experience
Expert in SQL for data transformation, analysis, and debugging
Deep knowledge of Airflow and orchestration best practices
Proficient in DBT (data modeling, testing, release workflows)
Experience with GCP (BigQuery, GCS, Composer); AWS familiarity is a plus
Strong grasp of data governance, observability, and privacy standards
Excellent written and verbal communication skills
Nice to have
Experience working with digital marketing and performance data, including:
Google Ads, Meta (Facebook), TikTok, Taboola, Outbrain, Google Analytics (GA4)
Familiarity with BI tools like Tableau or Looker
Exposure to attribution models, media mix modeling, or A/B testing infrastructure
Collaboration experience with data scientists or machine learning workflows
Perks:
● Day off on the 3rd Friday of every month (one long weekend each month)
● Monthly Wellness Reimbursement Program to promote health well-being
● Monthly Office Commutation Reimbursement Program
● Paid paternity and maternity leaves
