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
1.    Own ingestion and modeling of data from Meta Ads (Facebook) and other digital marketing platforms
2.    Build datasets that support:
·    Campaign performance tracking
·    Lead funnel analysis
·    Attribution and conversion tracking
3.    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
    Define success metrics tied to revenue and performance

•    Own key use cases such as:
    Lead funnel optimization
    Campaign attribution
    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 models
•    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