Senior Analytics Engineer

pbThis position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Analytics Engineer – Marketing Data based in Belgium. /b /p pJoin a data-driven environment where analytics engineering plays a key role in transforming marketing data into actionable business insights.br/In this role, you will design and optimize data models that support marketing analytics and business decision-making.br/You will work extensively with Google Analytics data, Snowflake, SQL, and Python to build reliable, scalable data solutions.br/Partnering with business stakeholders, you will translate complex requirements into clear technical deliverables.br/You will help ensure data quality, consistency, and accuracy throughout the entire data pipeline.br/Working within a collaborative, version-controlled development environment, you will contribute to robust engineering practices and continuous improvement.br/This opportunity is ideal for an experienced analytics engineer who combines strong technical expertise with business understanding and a proactive, problem-solving mindset. /p h3Accountabilities /h3 ul liDesign, develop, and maintain scalable data models, transformations, and materializations in Snowflake to support marketing analytics and business reporting. /li liWork hands‑on with Google Analytics data in a production environment, ensuring that marketing data is accurately structured and readily available for analysis. /li liDevelop, review, troubleshoot, and optimize SQL queries and Python code to improve data processing, reliability, and performance. /li liAnalyze API documentation and translate endpoints, objects, fields, and identifiers into practical data integration solutions aligned with business requirements. /li liImplement and maintain data validation practices across multiple stages of data pipelines to ensure data integrity, consistency and accuracy. /li liApply Git-based development workflows, including version control, code reviews, testing, and CI/CD practices to maintain high engineering standards. /li liCollaborate with stakeholders to gather requirements, clarify ambiguous business needs, structure discussions, and translate findings into precise, actionable technical specifications. /li liIdentify opportunities to improve data models, transformation logic, pipeline reliability, and overall analytics engineering processes. /li /ul h3Requirements /h3 ul liAt least 5 years of relevant professional experience in analytics engineering, data engineering, marketing data, or a closely related field. /li liHands‑on professional experience working with Google Analytics data in a business or production environment. Academic coursework, certifications, or self‑directed projects alone do not meet this requirement. /li liProfessional experience supporting data initiatives within a retail or e‑commerce environment. /li liAdvanced SQL skills, including experience designing fit‑for‑purpose data models, transformations, and materializations in Snowflake. /li liWorking proficiency in Python, with the ability to read, evaluate, debug, troubleshoot, and improve code written by others. /li liExperience interpreting API documentation and mapping API endpoints, objects, fields, and identifiers to business and technical requirements. /li liPractical experience with Git and version‑controlled development workflows, including code reviews, testing, and CI/CD. /li liStrong understanding of data quality and validation techniques across different stages of a data pipeline. /li liExcellent stakeholder management and requirements‑gathering skills, with the ability to bring structure to ambiguous discussions and turn business needs into clear technical solutions. /li liExceptional written and verbal communication skills in English, with the ability to communicate technical concepts clearly to both technical and non‑technical audiences. /li liA proactive, analytical, and detail‑oriented mindset, combined with strong problem‑solving skills and the ability to work effectively in a remote environment. /li /ul h3Benefits /h3 ul libRemote work: /b Work remotely from Anywhere, offering flexibility in your working environment. /li libLong‑term engagement: /b An opportunity to contribute to ongoing data engineering and marketing analytics initiatives through a long‑term contract. /li libTechnical impact: /b Work with modern data technologies, including Snowflake, SQL, Python, Google Analytics, and API integrations. /li libBusiness exposure: /b Collaborate with stakeholders to solve meaningful business challenges and support data‑informed decision‑making. /li libProfessional development: /b Strengthen your expertise in analytics engineering, data modeling, marketing data, and scalable data pipeline development. /li /ul pWe appreciate your interest and wish you the best /p