Join Credicorp Capital and take the lead in executing technical data and analytics initiatives, transforming business needs into scalable, reliable data solutions that adhere to corporate standards. As the Data Tech Lead, your mission is to ensure the successful technical implementation of data projects, guiding engineering teams from requirement analysis to production deployment while ensuring quality, performance, and sustainability of the solutions.Your goal is to design, oversee, and evolve integration, modeling, and data processing solutions, promoting best practices in engineering, DataOps, and architecture in coordination with architects, data governance, product owners, and technology teams.Main ResponsibilitiesDesign and lead the implementation of data integration and processing solutions (ETL/ELT) for both structured and unstructured data.Define and promote technical standards, architectural guidelines, and best practices in data engineering.Supervise the design and implementation of analytical and integration data models.Ensure the scalability, reliability, and quality of data pipelines in production environments.Actively participate in the technical planning of data projects, estimating efforts, risks, and dependencies.Monitor the technical progress of initiatives, identifying improvement opportunities and mitigating risks.Lead and technically support data engineers, aiding their development and accelerating their onboarding process.Coordinate technical relationships with external vendors and teams within the operational model.Ensure the correct application of CI/CD practices, DataOps, and automated testing in data solutions.Experience and SkillsAt least 1 year of experience as a Technical Lead in Data or Analytics projects.Experience in data integration and processing using Azure Data Factory and Databricks.Design and implementation of complex data integration solutions.Solid experience in data modeling.Over 3 years of experience working with relational databases (PostgreSQL, MySQL, Oracle, SQL Server), analytical databases (Redshift, BigQuery), and NoSQL databases (MongoDB, Redis).Experience applying best practices in CI/CD, DataOps, and automated testing.Experience in optimizing and tuning data processes.Strong analytical capabilities and problem-solving orientation.Clear and effective communication with stakeholders.
Mar 3, 2026