• ETL pipeline development — Build and maintain data ingestion pipelines that move data reliably from source into the warehouse. Own the infrastructure end-to-end. • Data transformation and table logic — Build and maintain transformation models — client-specific and shared. Handle schema changes, new table configurations, and the ongoing queue of transformation requests. • Data quality and anomaly detection — Own data quality monitoring end-to-end: setup, threshold tuning, alert triage, and fixes. Extend coverage through assertions and automated alerting. Turn reactive monitoring into proactive coverage. • Client onboarding infrastructure — Every new Lahzo client gets a dedicated cloud project, service accounts, permissions, and registered data pipelines. You own this process from infrastructure provisioning to first clean pipeline run. • Pipeline reliability and debugging — Understand the full data flow from raw event ingestion through final reporting tables. Debug issues across the stack end-to-end. • Ad hoc data requests — First responder for data requests from internal teams — confirming requirements, making schema or pipeline changes, and keeping the queue clear so the team stays focused on higher-leverage work.

Role Description We at Coforge are hiring Position (21826) for an experienced Tech Lead – Data Engineering with 8–10 years of overall experience to lead the design and development of modern data pipelines and platforms. In this role, you will architect and oversee ETL/ELT pipelines using Matillion, Snowflake, AWS, Python, and SQL, ensuring scalable and high-performance data solutions. You will combine hands-on technical work with leadership responsibilities, guiding a team of engineers and collaborating across functions. Bilingual fluency in English and Spanish is required. Responsibilities - Design & Develop Data Pipelines: Lead the end-to-end design, development, and optimization of ETL/ELT pipelines and data integration workflows using Matillion and Snowflake on AWS, ensuring data is clean, reliable, and readily accessible for analytics. - Technical Leadership: Own architectural decisions for the data platform and warehouse. Provide hands-on coding as well as mentorship, code reviews, and technical guidance to the data engineering team to uphold best practices and high coding standards. - Data Warehouse Architecture: Oversee the architecture of a modern cloud Data Warehouse solution. Implement data modeling and schema design that supports large-scale, scalable analytics and adheres to performance and security standards. - Cross-Functional Collaboration: Work closely with cross-functional teams (e.g., Data Science, Analytics, Product, DevOps) to translate business requirements into technical solutions. Ensure the data engineering strategy aligns with broader organizational goals. - AI/ML Integration: Collaborate with data science and AI teams to integrate machine learning and AI use cases into the data platform. Ensure that data pipelines and platforms can support AI/ML-driven applications (e.g., providing prepared datasets, enabling model training and inference), even though this role is not focused on model development. - Quality & Performance Assurance: Establish data quality checks, monitoring, and alerting within pipelines. Optimize ETL processes for efficiency (tuning SQL queries, managing resource usage) and ensure high availability and reliability of data workflows. Qualifications - Data Pipeline & ETL Tools: Expert hands-on skills in building ETL/ELT pipelines with Matillion (or similar ETL orchestrators) and deep proficiency in Snowflake data warehousing. - Programming & Database: Strong programming ability in Python and advanced SQL expertise for data transformation, analysis, and performance tuning. Solid understanding of relational and non-relational data stores; able to design efficient database schemas. - Cloud & Modern Data Stack: Extensive experience with AWS (and related data services) for developing and deploying data infrastructure. Familiarity with modern Data Warehouse architectures and tools in a cloud environment (e.g., data lakes, columnar storage, etc.). - Technical Leadership & Collaboration: Proven ability to lead engineering teams – excellent skills in technical mentoring, code review, and project leadership. Strong communication skills for collaborating with diverse stakeholders and driving cross-team initiatives. - AI/ML Concepts: Working knowledge of AI/ML concepts as they apply to data engineering (e.g., data preparation for machine learning, enabling ML model pipelines). Able to engage with data scientists to ensure the data platform effectively supports analytics and AI use cases. Requirements - Experience: 8-10 years - Location: Hermosillo, Mexico - Mode: Remote Company Description At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

• Desenvolver, implementar e manter pipelines de ingestão, transformação e disponibilização de dados; • Construir e evoluir processos de integração entre diferentes fontes de dados internas e externas; • Desenvolver e manter modelos de dados conceituais, lógicos e físicos, garantindo estrutura adequada para armazenamento e consumo das informações; • Realizar tratamento, consolidação e enriquecimento de dados para suportar necessidades analíticas e operacionais do negócio; • Garantir a qualidade, integridade, disponibilidade e rastreabilidade dos dados por meio de controles, validações e monitoramento contínuo; • Integrar dados provenientes de bancos de dados, APIs, sistemas corporativos, plataformas cloud e demais fontes de informação; • Disponibilizar dados para consumo por áreas de negócio, Analytics, Business Intelligence, Ciência de Dados e Inteligência Artificial; • Apoiar iniciativas de governança de dados, padronização de informações e evolução da arquitetura de dados corporativa; • Contribuir para a melhoria contínua dos processos, ferramentas, metodologias e soluções de engenharia de dados; • Participar da avaliação e implementação de novas tecnologias relacionadas à gestão, processamento e armazenamento de dados; • Levantar, compreender e traduzir necessidades de negócio em soluções de dados; • Atuar de forma colaborativa com equipes multidisciplinares, contribuindo para o compartilhamento de conhecimento e evolução das práticas da área.

Leega is a company dedicated to providing efficient, innovative service to its clients — and our greatest asset is our people. Our culture is inspiring and our values guide daily life: ethics and transparency, commitment to quality, teamwork, economic, social and environmental responsibility, human relations, and credibility. We seek innovative professionals who are motivated by challenges and focused on results. If you are looking for a dynamic, supportive company that invests in employees through continuous training, Leega is the place for you! >> LEEGA IS FOR EVERYONE — we will be very happy to have you on our team. Come be part of our story and help build our future. Register for our openings now!