[Hiring] Data Engineer L3 @Forbes Advisor

Role Description

• Data Engineering & Pipelines
  • Design, build, and maintain robust data pipelines for social marketing and product data sources (APIs, event streams, batch systems)
  • Develop scalable ETL/ELT workflows / microservices using Python and SQL
  • Ensure high data quality, reliability and observability across pipelines
  • Optimize data models for analytics and reporting use cases
• Marketing & Ad Platform Data
  • Own ingestion and modeling of data from Meta Ads (Facebook) and other digital marketing platforms
  • Build datasets that support campaign performance tracking, lead funnel analysis, attribution and conversion tracking
  • Understand key concepts such as campaign structure (campaign/ad set/ad level), bidding & optimization signals, attribution windows, pixel/event tracking.
• Business Understanding & Collaboration
  • Translate business requirements from marketing, growth and product teams into scalable data solutions
  • Define success metrics tied to revenue and performance
  • Enable self-serve analytics through well-structured datasets
• Data Quality & Governance
  • Implement validation checks, monitoring and alerting for pipelines
  • Ensure consistency across different marketing data sources
  • Maintain clear documentation of data models and pipelines
• Business Collaboration & Use Case Ownership
  • Work closely with marketing, growth, and analytics teams to understand real-world use cases and define success metrics tied to revenue and performance
  • Own key use cases such as lead funnel optimization, campaign attribution and revenue reporting and forecasting
  • Ensure data enables decision-making, not just reporting
• Engineering Standards & Best Practices
  • Design and implement modular, reusable microservices that enable the scalable development of data products.
  • Drive standardization through well-architected, loosely coupled services that can be leveraged across multiple use cases.
  • Uphold high standards in code quality and modularity, pipeline reliability and monitoring, documentation and data contracts
  • Contribute to shared frameworks and reusable components
  • Promote best practices across the data engineering team

Qualifications

• Core Technical Skills
  • Strong proficiency in Python (must-have)
  • Advanced SQL skills for large-scale data processing
  • Hands-on experience with data ingestion from APIs (rate limits, pagination, retries)
  • Experience with data orchestration tools (e.g., Airflow or equivalent)
  • Familiarity with cloud data platforms (BigQuery, etc.)
  • Experience building scalable data ingestion systems
  • Familiarity with microservices-style or modular data systems
  • Strong understanding of performance and cost optimization
• Ad Platform Knowledge
  • Solid understanding of Meta Ads platform fundamentals
  • Familiarity with campaign hierarchy and metrics (CTR, CPC, CPA, ROAS), conversion tracking and attribution model, Lead generation workflows and funnel metrics
  • Ability to interpret marketing data beyond surface-level metrics
  • Exposure to event tracking systems (GA4, Snowplow, etc)
• Good to Have
  • Experience with other ad platforms (Google Ads, Bing Ads, etc.)
  • Knowledge of data modeling best practices (e.g., star schema, dbt)
  • Experience with real-time or near real-time data pipelines

Benefits

• 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