Data Engineer L3

Responsibilities:

1. Data Engineering & Pipelines

• Design, build, and maintain robust data 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

2. 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.

3. 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

4. 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

5. 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

6. 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

Required Skills & Qualifications

1. 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

• 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

What Success Looks Like

• Reliable, scalable pipelines for marketing data ingestion
• High-quality datasets enabling accurate campaign and lead analysis
• Strong partnership with marketing teams, translating business needs into data solutions
• Improved visibility into lead quality, attribution and campaign performance
• Clear ownership of end-to-end data use cases, not just components

Why Join Us

• Work at the intersection of data engineering and growth marketing
• Solve high-impact problems in performance marketing and attribution
• Own meaningful data products end-to-end
• Influence both technical architecture and business outcomes
• Be part of a team that values ownership, impact and engineering excellence

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