Job
Description
Data Engineer About US FICO, originally known as Fair Isaac Corporation, is a leading analytics and decision management company that empowers businesses and individuals around the world with data-driven insights. Known for pioneering the FICO® Score, a standard in consumer credit risk assessment, FICO combines advanced analytics, machine learning, and sophisticated algorithms to drive smarter, faster decisions across industries. From financial services to retail, insurance, and healthcare, FICO's innovative solutions help organizations make precise decisions, reduce risk, and enhance customer experiences. With a strong commitment to ethical use of AI and data, FICO is dedicated to improving financial access and inclusivity, fostering trust, and driving growth for a digitally evolving world. The Opportunity “As a Data Engineer on our newly formed Generative AI team, you will work at the frontier of language model applications, developing novel solutions for various areas of the FICO platform to include fraud investigation, decision automation, process flow automation, and optimization. You will play a critical role in the implementation of Data Warehousing and Data Lake solutions. You will have the opportunity to make a meaningful impact on FICO’s platform by infusing it with next-generation AI capabilities. You’ll work with a dedicated team, leveraging your skills in the data engineering area to build solutions and drive innovation forward. ”. What You’ll Contribute Perform hands-on analysis, technical design, solution architecture, prototyping, proofs-of-concept, development, unit and integration testing, debugging, documentation, deployment/migration, updates, maintenance, and support on Data Platform technologies. Design, develop, and maintain robust, scalable data pipelines for batch and real-time processing using modern tools like Apache Spark, Kafka, Airflow, or similar. Build efficient ETL/ELT workflows to ingest, clean, and transform structured and unstructured data from various sources into a well-organized data lake or warehouse. Manage and optimize cloud-based data infrastructure on platforms such as AWS (e.g., S3, Glue, Redshift, RDS) or Snowflake. Collaborate with cross-functional teams to understand data needs and deliver reliable datasets that support analytics, reporting, and machine learning use cases. Implement and monitor data quality, validation, and profiling processes to ensure the accuracy and reliability of downstream data. Design and enforce data models, schemas, and partitioning strategies that support performance and cost-efficiency. Develop and maintain data catalogs and documentation, ensuring data assets are discoverable and governed. Support DevOps/DataOps practices by automating deployments, tests, and monitoring for data pipelines using CI/CD tools. Proactively identify data-related issues and drive continuous improvements in pipeline reliability and scalability. Contribute to data security, privacy, and compliance efforts, implementing role-based access controls and encryption best practices. Design scalable architectures that support FICO’s analytics and decisioning solutions Partner with Data Science, Analytics, and DevOps teams to align architecture with business needs. What We’re Seeking 7+ years of hands-on experience as a Data Engineer working on production-grade systems. Proficiency in programming languages such as Python or Scala for data processing. Strong SQL skills, including complex joins, window functions, and query optimization techniques. Experience with cloud platforms such as AWS, GCP, or Azure, and relevant services (e.g., S3, Glue, BigQuery, Azure Data Lake). Familiarity with data orchestration tools like Airflow, Dagster, or Prefect. Hands-on experience with data warehousing technologies like Redshift, Snowflake, BigQuery, or Delta Lake. Understanding of stream processing frameworks such as Apache Kafka, Kinesis, or Flink is a plus. Knowledge of data modeling concepts (e.g., star schema, normalization, denormalization). Comfortable working in version-controlled environments using Git and managing workflows with GitHub Actions or similar tools. Strong analytical and problem-solving skills, with the ability to debug and resolve pipeline and performance issues. Excellent written and verbal communication skills, with an ability to collaborate across engineering, analytics, and business teams. Demonstrated technical curiosity and passion for learning, with the ability to quickly adapt to new technologies, development platforms, and programming languages as needed. Bachelor’s in computer science or related field Exposure to MLOps pipelines MLflow, Kubeflow, Feature Stores is a plus but not mandatory Engineers with certifications will be preferred Our Offer to You An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others. The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences. Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so. An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie. Show more Show less
