Data Engineer In Test

We are Two Circles. We are a Sports & Entertainment Marketing business. We grow audiences and revenues. We do that by knowing fans best. We work with clients to help them understand & influence what their fans are doing – the way fans spend their money, the events that fans attend, the channels fans respond to, the content fans watch and more.

And we use the understanding this gives us to help our clients grow. Grow their audiences and grow their revenues - both direct to consumer and business to business revenues. Our platforms and services are trusted by over 1000 clients globally, including the English Premier League, Red Bull, UEFA, VISA, the NFL, Nike and Amazon. We are over 1000 people, based out of 15 offices, and we deliver work for sports and entertainment businesses of all shapes and sizes all over the world.

Two Circles is looking for a "Data Engineer in Test" to join our dynamic KORE Intelligence Platform team. In this role, you'll be a key part of our Partnership Intelligence >
Measurement Team that specializes in the ingestion, transformation, and storage of large-scale social and broadcast data.

The Data Engineer In Test (Python & SQL) is responsible for ensuring the accuracy of data and the health, reliability, and observability of analytics and data systems. This role focuses on building monitoring, alerting, and validation frameworks that provide early detection of data issues, pipeline failures, performance degradation, and system-level risks.

You will develop SQL-based data quality checks, Python-driven automation, and reliability safeguards to monitor data pipelines, transformations, and analytics outputs, while also tracking system health signals such as freshness, volume anomalies, latency, and job stability. Working closely with data engineering, analytics, and platform teams, you will help define reliability standards, SLAs, and alerting strategies that ensure analytics systems remain dependable and production-ready.

Experience with automation and UI testing frameworks—such as Playwright, Selenium, Cypress, or similar tools is considered a strong asset. This includes validating analytics dashboards, alerting workflows, and end-to-end data flows through user-facing interfaces, helping ensure that system behavior aligns with expectations beyond the data layer.

This role is well suited for an engineer who takes a holistic view of reliability, combining data correctness, system resilience, and automated validation across both backend systems and user-facing surfaces.

• Advanced SQL skills for building data quality checks, anomaly detection, alerting logic, and monitoring queries, ideally in Snowflake or similar cloud data warehouses.
• Strong Python proficiency for automation, validation frameworks, orchestration, and system health checks.
• Experience designing and maintaining data quality and reliability frameworks, including freshness, completeness, accuracy, volume, and schema validation.
• Solid understanding of data pipelines and analytics workflows, including ETL/ELT processes, transformations, and downstream consumption.

• Experience monitoring system and pipeline health, including job failures, latency, throughput, and SLA adherence.
• Familiarity with alerting and observability concepts, such as thresholds, anomaly detection, alert fatigue reduction, and incident prioritization.
• Ability to perform root-cause analysis and contribute to remediation and prevention of recurring issues.

• Experience with automation and testing frameworks such as Playwright, Selenium, Cypress, or similar tools is a strong asset.
• Understanding of end-to-end testing concepts, including validation of analytics dashboards, alerts, and user-facing data flows.
• Ability to integrate automated checks into CI/CD or scheduled workflows.

• Proficiency with version control (Git) and collaborative development workflows.
• Experience writing maintainable, well-documented code and SQL.
• Familiarity with CI/CD pipelines, task schedulers, or orchestration tools (e.g., Airflow, dbt, or similar) is beneficial.

• St…