Data Engineer L3

Required Skills & 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
• 2. 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

What Success Looks Like

Why Join Us

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
• 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 looking for a highly skilled Data Engineer (L3) with strong expertise in Python, data ingestion pipelines and marketing data systems, particularly with the Meta Ads ecosystem. This role sits at the intersection of data engineering and social/native platforms, enabling scalable data pipelines, high-quality datasets, and lead generation and business decision-making.
• This role goes beyond building pipelines - will be responsible for:
• Designing scalable data architecture
• Driving business outcomes (revenue, lead quality, conversion efficiency)
• Owning how data is used, trusted and acted upon
• The ideal candidate will not manage campaign buying or bidding directly but must clearly understand ad platform mechanics, attribution models and lead quality scores and will work closely with the Data Lead / Engineering Lead, acting as a key contributor in shaping solutions, making technical decisions, and delivering high-impact data products..