Data Engineer

The Data Engineer works as part of the Data Engineering team. This position is responsible for building and maintaining the data infrastructure that supports our internal products. This role involves collaborating closely with Product Managers and Designers to understand requirements and translate them into effective data warehousing solutions. The Data Engineer will also work with Development teams to establish and enforce best practices for data processing and modeling. This role is essential for ensuring data accuracy, efficiency, and scalability, ultimately impacting client retention and satisfaction. Your key responsibilities include: Design, build, and maintain scalable and reliable data pipelines using Python, PySpark, and SQL. Develop and optimize data transformations and ETL processes, ensuring data accuracy and relevance for our internal reporting. Collaborate with Leadership Team to understand data requirements and deliver effective solutions that meet client needs. Build scalable and discoverable data models in SQL and maintain detailed documentation for each. Implement data quality checks and monitoring to ensure data accuracy and integrity, directly impacting the quality of data our clients receive. Optimize data storage and retrieval for performance and cost efficiency, considering the demands of client access and reporting. Contribute to cluster optimization and maintenance, ensuring efficient resource utilization. Document data engineering processes and best practices, with a focus on clear communication for both internal teams and, where appropriate, client-facing documentation. Collaborating in continuously improving the team’s working practices and development processes. Annual OKRs will be set at the individual level to contribute to the OKRs of the Business unit, Team and the Company. You will be successful if you have 2-4 years of experience in Data Engineering, proficiency in Python, PySpark, SQL, Databricks/DBT and English proficiency.