Data Engineer (L2)

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, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. 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, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. We bring 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.

At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most.

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.

Role Overview

We are looking for a Data Engineer (L2) with solid experience in Python and data ingestion pipelines, and exposure to digital marketing data, particularly the Meta Ads ecosystem.

In this role, you will contribute to building and maintaining data pipelines that power marketing analytics, campaign reporting, and lead analysis. You will work closely with senior engineers and business teams to support data needs across performance marketing and growth.This role does not involve campaign execution (buying/bidding), but requires a working understanding of ad platforms, marketing metrics, and lead funnels.

Key Responsibilities

Data Engineering & Pipelines

· Build and maintain data ingestion pipelines from APIs and other data sources

· Write efficient Python and SQL for data transformation and processing

· Support ETL/ELT workflows, microservices and ensure timely data availability

· Troubleshoot pipeline failures and assist in performance improvements

Marketing Data Support

· Assist in ingestion and modeling of data from Meta Ads and similar platforms

· Help create datasets for:

o Campaign performance reporting

o Lead funnel tracking

· Develop familiarity with:

o Campaign structure (campaign/ad set/ad level)

o Basic performance metrics (CTR, CPC, CPA)

o Conversion tracking concepts

Business Collaboration

· Work with marketing and analytics teams to understand data requirements

· Support analysis related to lead quality and campaign performance

· Help translate business needs into data queries and datasets

Data Quality & Maintenance

· Implement basic data validation checks

· Monitor pipelines and resolve data issues

· Maintain documentation for pipelines and datasets

Required Skills & Qualifications

Core Technical Skills

· Proficiency in Python (data processing, API handling)

· Strong SQL skills

· Experience with data ingestion from APIs (basic handling of pagination, retries)

· Familiarity with workflow orchestration tools (e.g., Airflow or similar)

· Exposure to cloud data warehouses (BigQuery, etc.)

Ad Platform Exposure

· Basic understanding of Meta Ads platform concepts

· Familiarity with:

o Marketing metrics (CTR, CPC, conversions)

o Lead generation and funnel basics

· Willingness to learn deeper AdTech concepts

Soft Skills

· Good problem-solving and debugging skills

· Ability to work in a collaborative, cross-functional environment

· Clear communication of technical work and issues

Good to Have

· Exposure to other marketing platforms (Google Ads, etc.)

· Experience with tools like dbt or similar transformation frameworks

· Understanding of event tracking (GA4, etc.)

What Success Looks Like

· Reliable execution of data pipelines with minimal supervision

· Accurate and timely delivery of marketing datasets

· Growing understanding of marketing data and business use cases

· Effective collaboration with senior engineers and stakeholders

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

Any degree