Data Engineer II- Marketing Science

As a Data Engineer in the Marketing Data team, you will play a crucial role in enhancing the data platform to drive world-class marketing insights. Working alongside data engineers, analysts, data scientists, and marketing stakeholders, your focus will be on ensuring the reliability, scalability, and operational excellence of data products that underpin our marketing strategy. Your responsibilities will include: - Maintaining and optimizing data pipelines that process high volumes of marketing data from various sources such as digital platforms, CRM, and ad tech tools. - Developing robust monitoring, alerting, and testing frameworks to uphold data quality and operational reliability across marketing datasets. - Building and enhancing data models and infrastructure to support marketing attribution, audience targeting, A/B testing, and funnel analysis. - Facilitating self-service data access for marketing teams through the delivery of well-documented and performant data products and interfaces. - Collaborating with cross-functional partners including product managers, marketing analysts, campaign managers, and data scientists globally to drive data-driven decision-making. Your contributions will empower marketing teams to experiment, iterate, and make informed decisions with agility and confidence. To be successful in this role, you should meet the following job requirements: - Minimum 5 years of hands-on experience in data engineering, either as a Data Engineer or Software Engineer focusing on data pipelines and products. - Bachelor's degree in Computer Science, Computer or Electrical Engineering, Mathematics, or related field, or equivalent experience. - Proficiency in at least one programming language such as Java or Python. - Experience in building production data pipelines in the cloud, establishing data lakes, and implementing server-less solutions. - Hands-on experience with schema design, data modeling, and E2E system design. - Familiarity with tools like CDC, Kafka, Airflow, Snowflake, DBT, or equivalent, and practical knowledge in building data platform capabilities. - Experience with big data, working across different time zones, and a plus in experimentation, statistics, and A/B testing. Please note that if your application progresses, pre-employment screening may be conducted to verify your qualifications and suitability for the position as permitted by applicable law.,