Role Description - Monitor and support daily ELT pipelines and reporting processes. - Design, document, and maintain data warehouse models as source systems evolve. - Develop and maintain semantic-layer and business intelligence data models. - Support month-end reporting and recurring business processes. - Improve and prepare data assets for AI-enabled workflows and automation initiatives. - Design data transformations that enhance data quality, consistency, accessibility, and usability. - Troubleshoot data issues and support analytics requests across the organization. - Serve as the primary technical resource for analytics infrastructure and reporting systems. - Prepare internal metrics, analytics, and leadership reporting. - Collaborate with stakeholders on data-driven initiatives and continuous improvements. Qualifications - 4+ years of experience in analytics engineering, data engineering, business intelligence, analytics, or related fields. - Strong understanding of data warehousing, dimensional modeling, and semantic-layer concepts. - Experience building and maintaining ELT/ETL pipelines. - Strong SQL and data modeling skills. - Experience working with software engineering workflows and source control. - Strong communication, documentation, and stakeholder management skills. - Hands-on experience with dbt, Amazon Redshift, Amazon QuickSight, AWS, Python, GitHub, Docker, and SQL. - Advanced English. Requirements - Experience with CI/CD workflows. - Knowledge of data governance practices and experience in healthcare, finance, or other regulated industries. Benefits - Great Place To Work certification. - A company with more than 15 years of experience. - Work with world-class clients and long-term projects. - English scholarships for an external institute. - English classes with company teachers. - State-of-the-art tools and resources. - Certifications for your professional growth. - Recreation and leisure activities. - Compliance with the regulations and labor rights of your region.

• Work From Anywhere in LATAM and the Philippines • Design clean schemas, write efficient SQL, and optimize Postgres performance • Extend and evolve the Postgres schema across recruiting, candidates, and business operations • Build SQL views and derived tables for reporting and AI • Optimize query performance through indexing, partitioning, and execution-plan analysis • Complete schema audit with top-priority fixes shipped and measurable performance gains within the first 3-6 months

• Розробка та підтримка масштабованих ETL/ELT-процесів для збору, трансформації та завантаження даних • Проєктування та впровадження надійних пайплайнів даних для обробки інформації як у режимі реального часу (real-time), так і пакетної обробки (batch processing) • Забезпечення якості, цілісності та доступності даних для аналітичних і операційних систем • Оптимізація продуктивності SQL-запитів та архітектури баз даних • Автоматизація розгортання та моніторингу компонентів інфраструктури даних • Тісна співпраця з командами аналітики, розробки та бізнесу для впровадження рішень, заснованих на даних

• Develop, maintain, and optimize legacy ETL and DWH processes. • Work hands-on with Oracle, Teradata, SQL, PL/SQL, and stored procedures. • Develop IBM DataStage or similar ETL platforms such as Informatica or Ab Initio. • Participate in legacy-to-modern data migration projects. • Analyze existing data structures and map them to modern architectures. • Build and manage data pipelines using Apache Spark. • Read and write data from object storage environments such as AWS S3. • Contribute to technology evaluation, PoC studies, and future platform decisions. • Define technical standards and provide architectural guidance to data and analytical teams.