data engineer in fintech

The company provides financial services.

• Interpret and analyze complex data-related problems;
• Conceive, prioritize, and plan data projects aligned with organizational goals;
• Develop and implement databases, data collection systems, data analytics solutions, and other strategies to optimize statistical efficiency and quality;
• Acquire data from primary and secondary sources and maintain databases and data systems;
• Identify, analyze, and interpret trends and patterns in complex datasets;
• Ensure data quality, accuracy, and integrity;
• Maintain comprehensive data science and analytics documentation;
• Develop ETL processes using Python;
• Collaborate with team members and stakeholders to identify opportunities where data can create business value;
• Develop and implement data science infrastructure, including experiment tracking, feature stores, A/B testing platforms, and other related tools and frameworks.

• Hands-on experience with Python;
• Hands-on experience writing SQL queries;
• Strong knowledge of database design and development, data modeling, data mining, and data segmentation;
• Experience building processes that support data transformation, data structures, metadata management, dependency management, and workload management;
• Bachelor’s degree in Mathematics, Statistics, Data Science, Computer Science, or a related field;
• Strong analytical skills with the ability to collect, organize, analyze, and present large amounts of information accurately and effectively;
• Nice to have: knowledge of Databricks, Dataflow, or Apache Spark; knowledge of Prefect, MLflow, or similar tools; knowledge of ML/DL libraries; experience deploying machine learning or deep learning solutions.

• Competitive salaries and benefits;
• Supportive and collaborative environment;
• Unlimited opportunities for growth and development.