• Toma de requisitos, desarrollo, pruebas funcionales y validación de soluciones de datos. • Diseño e implementación de procesos de carga e integración de datos con herramientas ETL, especialmente PowerCenter, IDQ o DEI. • Promoción a producción y mantenimiento de procesos, asegurando su correcta operativa. • Trabajo con bases de datos y plataformas como BigQuery, Cloudera/Hive y SQL Server, incluyendo documentación técnica.

• Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets. • Develop tools and frameworks to streamline data integrations and improve scalability. • Define the technical vision for DC data architecture and mentor engineers. • Manage external contractors to ensure the team delivers high-quality, practical solutions. • Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.

• Define and drive the data engineering technical strategy, architecture decisions, and platform roadmap aligned to company objectives • Lead and deliver large-scale, complex data initiatives—spanning multiple teams and iterations—from ambiguous problem definition through production deployment • Design robust, scalable data architectures (batch and streaming) that support Kueski's long-term business needs at scale • Demonstrated success shaping and executing an AI-centric data strategy that leverages the latest AI technologies to accelerate value delivery, enable trusted self-service data consumption, and strengthen data quality, governance, and organizational decision-making. • Identify the limits of existing tools or processes; lead the design and build of new capabilities when current solutions fall short • Shape, standardize, and champion data engineering methodologies, best practices, and technical standards for the team and department • Develop and own CI/CD pipelines and infrastructure-as-code for reliable, automated data platform operations • Drive data quality, observability, and governance programs across the data platform • Apply data cleansing techniques to facilitate data consumption and quality across the platform • Partner cross-functionally with Data Science, ML, Analytics, Platform, and Product teams to deliver data-driven solutions end-to-end • Represent data engineering in cross-organizational initiatives; support and lead efforts outside the core area of responsibility • Mentor and guide Data Engineers at all levels; constructively challenge assumptions and elevate team quality through code review, pairing, and coaching

Role Description We at Coforge are hiring Senior Snowflake Data Engineers with the following skill set. We are looking for two Senior Data Engineers (21999) to support our client in scaling their Data Engineering capabilities. The team is currently managing a backlog of ~170 projects, ranging from data infrastructure and database development to integrations and reporting initiatives. This is an excellent opportunity to work on high-impact, data-driven projects in a fast-paced, collaborative environment. - Design scalable and efficient data models and analytical cubes in collaboration with stakeholders. - Develop and maintain robust data pipelines using SQL and Python. - Integrate data models and data services through APIs. - Leverage Snowflake to build optimized, high-performance data solutions. - Collaborate with cross-functional teams to support data infrastructure, reporting, and analytics initiatives. - Ensure best practices in data architecture, modeling, and pipeline performance. - Contribute to continuous improvement of data engineering standards and practices. Qualifications - 5+ years of experience in Data Engineering or related roles. - Strong proficiency in SQL and Python. - Hands-on experience with Snowflake (minimum 1 year). - Solid experience in data modeling for analytical and reporting use cases. - Proven experience in API integrations. - Strong problem-solving skills and attention to detail. - Ability to work collaboratively in cross-functional teams. - Good communication skills and a proactive mindset. Requirements - Familiarity with AWS and cloud-based data solutions. - Experience working in environments with large backlogs or multiple concurrent data projects. - Exposure to modern data architectures and scalable pipeline design. Company Description At Coforge, we hire professionals based solely on their skills and qualifications. We are committed to building an inclusive workplace and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.