Data Engineer

Madgicx is transforming how eCommerce brands scale their digital advertising through AI-powered automation and intelligent optimization. Our platform helps thousands of companies make smarter decisions, automate complex workflows, and unlock growth with cutting-edge data and AI capabilities.

As we continue to expand our AI stack and real-time analytics, we're looking for a Data Engineer who is passionate about building reliable, scalable, and high-performance data infrastructure.

‍

As a Data Engineer at Madgicx, you will design, build, and maintain the data pipelines and models that power our AI agents, analytics, dashboards, and automated marketing solutions.

You'll work with streaming and batch systems, build production-grade transformations, and optimize our BigQuery warehouse to support massive datasets coming from Meta, Google, TikTok, and more.

This is a hands-on engineering role ideal for someone who loves solving complex data challenges, enjoys owning systems end-to-end, and wants to directly influence the future of AI-powered advertising.

‍

• Build and maintain real-time streaming pipelines ingesting advertising data from multiple platforms (Meta, Google, TikTok, etc.).
• Design event-driven architectures using Pub/Sub, Kafka, RabbitMQ, or similar technologies.
• Implement ELT transformations with dbt/Dataform and build analytics- and AI-ready data models.
• Optimize our BigQuery data warehouse for performance, cost-efficiency, and scalable growth.
• Create and maintain dimensional models, feature-store–ready datasets, and AI/ML-friendly schemas.
• Implement data quality frameworks, validation rules, freshness checks, and lineage tracking.
• Develop monitoring and alerting for pipeline health, cost anomalies, and SLA adherence.
• Contribute to best practices, documentation, and code reviews to ensure high engineering standards.
• Collaborate with Data Science, Backend, and Product teams to support product features and new AI capabilities.

• 3+ years of experience in production Data Engineering.
• Strong SQL proficiency (CTEs, window functions, performance tuning).
• Hands-on experience with BigQuery (preferred), Snowflake, or Redshift.
• Production experience with dbt, Dataform, or similar transformation frameworks.
• Strong Python skills for data processing and automation.
• Experience with streaming systems (Pub/Sub, Kafka, Dataflow, Apache Beam, RabbitMQ).
• Solid understanding of dimensional modeling and ELT best practices.
• Experience with GCP (preferred) or another cloud ecosystem.

‍

• Experience with data quality frameworks (Great Expectations, dbt tests, custom tools).
• Knowledge of data observability tooling and lineage tracking.
• Familiarity with Airflow, Cloud Composer, Dagster, or similar orchestration tools.
• Understanding of GDPR, PII masking, and data governance principles.
• Previous experience building feature stores or supporting AI/ML pipelines.

• Unlimited Time-Off Policy — because we trust you to manage your time responsibly.
• Annual Performance Review — structured growth, development plans, and compensation review every year.
• Real impact: Your pipelines power insights and automation affecting billions in ad spend.
• Cutting-edge tech: Streaming, large-scale warehouses, declarative transformations, and AI workloads.
• Ownership: Full responsibility for your data domains — from ingestion through consumption.
• Learning & growth: Budget for courses, conferences, and certifications.
• Flexible work culture: Remote-first environment with flexible hours.
• Competitive compensation package including equity and performance bonuses.