Implementing methods to improve data reliability and quality. Combining raw information from different sources to create consistent and machine-readable formats, developing and testing architectures that enable data extraction and transformation for predictive or prescriptive modeling. Developing and maintaining scalable data pipelines and building out new API integrations to support continuing increases in data volume and complexity. Collaborating with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization. Implementing processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.