Senior Engineer - Data Engineer

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Experience: 3+ years Role & Responsibilities Develop and maintain data models in Snowflake using dimensional modeling techniques such as star and snowflake schemas to support reporting and analytics requirements. Build, test, and document dbt models across staging, intermediate, and mart layers while following established development standards and best practices. Support Snowflake performance and cost optimization activities, including query tuning, warehouse monitoring, and efficient data storage practices. Design and maintain ELT/ETL pipelines to ingest and transform data from multiple sources such as ERP systems, APIs, flat files, and cloud platforms into Snowflake. Develop automation scripts and data processing workflows using Python and cloud-native services. Implement data quality validations, perform data reconciliation, and assist in maintaining data lineage and documentation. Work closely with business analysts, reporting teams, and stakeholders to understand data requirements and deliver reliable data solutions. Participate in code reviews, testing, deployment activities, and continuous improvement of data engineering processes. Experience Experience: 3+ years of experience in data engineering, analytics engineering, or a related role, with hands-on Snowflake and dbt experience in a production environment. Good understanding of Snowflake data warehousing concepts, including data modeling, SQL development, performance tuning, and data loading processes. Hands-on experience with dbt for model development, testing, documentation, and deployment. Strong SQL skills, including joins, CTEs, window functions, aggregations, and data transformation techniques. Proficiency in Python for data processing, automation, and API integration. Experience building and supporting ETL/ELT pipelines in cloud environments. Familiarity with BI and reporting tools such as Power BI or Tableau. Working knowledge of cloud platforms (AWS, Azure, or GCP) and related data services. Understanding of Git version control and CI/CD concepts. Must have skills: Data Modeling (Strong), Snowflake Good to have skills: ETL Concepts (Capable), Power BI (Capable), Python (Capable)