Data Engineer

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We are Rokt, a hyper-growth ecommerce leader. Rokt is the global leader in ecommerce, unlocking real-time relevance in the moment that matters most. Rokt's AI Brain and ecommerce Network powers billions of transactions connecting hundreds of millions of customers, and is trusted to do this by the world's leading companies. We are a team of builders helping smart businesses find innovative ways to meet customer needs and generate incremental revenue.

Leading companies drive 10-50% of additional revenue—and often all their profits—from the extra products or services they sell. This economic edge unleashes a world of possibilities for growth and innovation. The Rokt engineering team builds best-in-class ecommerce technology that provides personalized and relevant experiences for customers globally and empowers marketers with sophisticated, AI-driven tooling to understand consumers better. Our bespoke platform handles millions of transactions per day.

It considers billions of data points which give engineers the opportunity to build technology at scale, collaborate across teams, and gain exposure to a wide range of technology. At Rokt, we practice transparency in career paths and compensation. At Rokt, we believe in transparency, which is why we have a well-defined career ladder with transparent compensation and clear career paths based on competency and ability.

Rokt's stars constantly strive to raise the bar, pushing the envelope of what is possible.

Join Rokt as a Data Engineer on the Metrics team, you will architect the semantic and data layers that define how Rokt measures success. You'll transform raw product and GTM event streams into trusted, governed, analytics-ready models; codify business logic into reusable metric definitions; and build proactive monitoring to keep our "single source of truth" healthy and reliable 'll serve as metric steward for one or more business domains, owning the semantic layer and data models end-to-end.

You'll partner closely with engineers, product managers, data scientists, and GTM stakeholders across Rokt's Research & Development organization to enable self-serve insights and consistent decision-making.

• Model data for trust & reuse:
  Build modular, tested transformations (e.g. in Spark/Python) that convert raw logs into canonical datasets and marts powering experimentation, product analytics, and executive reporting.
• Own the metrics layer:
  Design and maintain a governed catalog of metrics and dimensions (e.g.Datahub) with clear definitions, lineage, and versioning.
• Operate reliable pipelines:
  Orchestrate and harden batch/stream pipelines (e.g., Airflow/Kafka/Spark) with SLAs, backfills, and cost-aware performance tuning.
• Proactive data quality:
  Implement unit/integration tests, anomaly detection, and monitoring (e.g Great Expectations/Monte Carlo/Bigeye) to catch metric drift and upstream integration issues before they reach users.
• Integration health visibility:
  Build dashboards/alerts for client conversion data health and integration metrics (e.g., EMQ, AQS), and drive root-cause analysis and remediation with partner teams.
• Enable self-serve analytics:
  Create intuitive dashboards and templates (e.g., Tableau) that expose the metric layer and unlock analysis for engineering, PM, and GTM users.
• Define logging standards:
  Partner with product/engineering to instrument event schemas and logging guidelines that improve downstream observability and data quality.
• Document & govern:
  Establish style guides, playbooks, and change-management processes for metric and model evolution (including deprecation and backfills).
• Raise the bar:
  Lead code reviews, mentor peers, and contribute to platform roadmaps across Rokt Research.

• 3-6+ years in data engineering / data warehousing roles building production-grade data models and metrics at scale.
• Expert SQL (Trino preferred) and solid Python for analytics engineering…