Analytics Engineer

Traffic Label is a fast-growing, data-driven technology company operating in the iGaming and affiliate marketing space, building scalable products focused on performance, analytics, and automation across global markets.

We are looking for an experienced Senior Analytics Engineer to join our Data Platform team and take end-to-end ownership of data solutions that drive business decisions.

This role sits at the intersection of data engineering and analytics, combining hands-on technical expertise with a strong understanding of business needs.

You will be responsible for the entire data lifecycle — from ingesting data from external sources and building reliable data models to delivering actionable insights through dashboards and reporting.

We are looking for someone who can independently translate complex business requirements into scalable, production-ready solutions, take ownership of delivery, and confidently leverage AI-powered development tools to improve efficiency while maintaining high standards of quality.

• End-to-End Data Delivery: Own the complete data lifecycle, from data ingestion and transformation to modelling, analysis, and reporting.
• Data Pipeline Development: Design, build, and maintain reliable pipelines integrating data from external systems into our cloud data warehouse.
• Data Modelling: Develop, test, document, and maintain scalable data models that ensure accuracy, consistency, and accessibility.
• Business Intelligence & Analytics: Transform complex datasets into meaningful dashboards, reports, and actionable business insights.
• Data Quality & Governance: Ensure data integrity and reliability throughout the entire data pipeline, from source systems to final reporting.
• Engineering Best Practices: Follow established development processes, including version control, code reviews, automated testing, CI/CD, and controlled deployments.
• AI-Assisted Development: Leverage AI coding agents to accelerate development while maintaining full accountability for code quality, accuracy, and production readiness.
• Stakeholder Collaboration: Work closely with business stakeholders to translate ambiguous requirements into clearly defined technical solutions, communicating priorities, trade-offs, and recommendations.
• Continuous Improvement: Identify opportunities to optimise data workflows, improve system performance, and enhance the overall reliability of the data platform.

Within your first few months, you will independently take a business requirement from concept to production - ingesting the necessary data, building reliable models, delivering actionable dashboards, and deploying the solution through established engineering processes.

You will demonstrate full ownership of your work, make informed technical decisions, and clearly communicate the reasoning behind your approach.

• Work Model: Fully Remote (EMEA)
• Department: Development
• Reporting to: CTO

• 5+ years of experience developing data pipelines and data models within modern cloud-based data environments.
• Advanced SQL skills and strong expertise in data modelling, from raw data ingestion to structured, well-documented datasets.
• Solid Python programming skills, particularly for data ingestion, automation, and pipeline development.
• Hands-on experience with workflow orchestration tools and scheduled data pipelines.
• Experience building dashboards, reports, and analytical solutions using modern BI tools.
• Strong understanding of software engineering best practices, including Git, code reviews, automated testing, and CI/CD pipelines.
• Practical experience using AI coding agents to improve development efficiency, with the ability to critically evaluate and validate AI-generated outputs.
• Ability to independently manage projects from initial requirements gathering through implementation and production deployment.
• Strong problem-solving skills, attention to detail, and a proactive approach to ensuring data accuracy and reliability.
• Excellent communication skills, with the ability to explain technical concepts and decisions clearly to both technical and non-technical stakeholders.
• Experience with Infrastructure as Code (IaC) and cloud infrastructure management.
• Knowledge of identity resolution and Master Data Management (MDM).
• Understanding of data governance principles, PII handling, and data masking.
• Experience optimising cloud data warehouse performance and managing infrastructure costs.

Our Technology Stack

Snowflake, dbt, Python, Airflow (Astronomer), AWS, Terraform, GitHub Actions, Omni, and Kiro AI agents.

• Impactful Work: Take ownership of meaningful data initiatives that directly influence business decisions and performance.
• Modern Technology Stack: Work with advanced cloud technologies, modern data engineering tools, and AI-powered development solutions.
• Autonomy & Ownership: Enjoy the freedom to independently scope, develop, and deliver solutions while taking responsibility for their outcomes.
• Collaborative Environment: Join a supportive, technically driven team that values transparency, knowledge sharing, and practical problem-solving.
• Professional Growth: Develop your expertise through challenging projects, continuous learning, and exposure to evolving technologies.
• Engineering Excellence: Work in an environment that prioritises clean code, reliable data, structured delivery processes, and continuous improvement.