Lead Data Engineer

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
 

Qualifications :

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

 

Additional Information :

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

Remote Work :

No

Employment Type :

Full-time