Role Description We are looking for someone to work in a team that thinks big, works with attention to detail, collaborates daily, and shares responsibility. We believe in autonomy, the exchange of different experiences, and solutions built together. Here, growth means sharing knowledge, respecting different ways of thinking, and building trusting relationships while delivering quality technology. If you identify with this way of working, come join us. What you will do: - Design and build end-to-end data pipelines in a modern cloud data platform; - Ingest data from APIs and RPA-based systems; - Structure and transform data across raw, staging, and curated layers; - Develop and deploy Python-based cloud functions/services; - Work with Google Cloud Platform (BigQuery and Cloud Storage); - Build and maintain CI/CD pipelines using Azure DevOps; - Provision and manage infrastructure using Terraform (Infrastructure as Code); - Automate data export and delivery to downstream and external systems; - Ensure data quality, performance, and reliability at scale. Qualifications - Fluent English; - Solid experience in cloud data engineering; - Strong proficiency in Python and SQL; - Experience building pipelines with REST API ingestion; - Hands-on experience with Google Cloud Platform (BigQuery, GCS, Cloud Functions); - Hands-on experience with Azure DevOps for CI/CD pipelines; - Working knowledge of Terraform / Infrastructure as Code; - Experience working with large-scale or semi-structured datasets; - Strong analytical mindset with a hands-on and collaborative approach. Requirements - Experience working with RPA-generated data; - Knowledge of data modeling and data warehousing; - Experience with data export/integration formats (CSV, JSON, file-based delivery); - Familiarity with API authentication methods (OAuth, API keys). Benefits - 🍽 Meal/Food Allowance - Caju multi-benefit card (credit format), offering flexibility for everyday needs. (CLT only) * - 🏥 Health Plan – Unimed - No waiting period or copayment for the holder. Possibility to include dependents (children, spouse, or stepchildren) with copayment. (CLT only) * - 🦷 Dental Plan – Uniodonto - Affordable options to include dependents. (CLT only) * - 💪 Wellhub - Access to gyms, physical activities, and wellness programs. - 🧘 Zenklub - For CLT: Two free sessions per month and special rates for additional sessions. For Cooperative/Contractor: Special rates for sessions. - 🛡 Life Insurance - More security for you and your family. (CLT only) * - 👶 Childcare Allowance - Financial support for Zallpers with children from 4 months to 6 years old, according to internal policy. (CLT only) * - 🎁 Baby Zallpy - A special gift to celebrate the arrival of new Zallpy babies. - 👥 Business Partner Support - Close and human-centered support from our People & Culture team throughout your journey at Zallpy. - 🌍 Volunteer Internal Communities - Diversity, Sports & Movement, and Technology. - 🎓 Educational Partnerships - Discounts on undergraduate and graduate programs, professional courses, and language schools. - ✈️ Experiences & Development - Participation in events, workshops, trips, and team-building activities. - 💼 Referral Program - Refer talents to Zallpy and receive bonuses from R$2,500 to R$5,000.

Role Description We at Coforge are hiring a Senior Data Engineer with the following skill set. - Design and implement scalable data pipelines using Databricks and Microsoft Fabric. - Build and maintain a Medallion Architecture (Bronze, Silver, Gold layers) to organize and process data across the organization. - Collaborate with the AI team to ensure high-quality data availability for RAG patterns and LLM components. - Develop and optimize data models that feed directly into the Microsoft Power Platform (Power BI). - Ensure data platform performance and reliability while maintaining a platform-agnostic approach where possible. Qualifications - Experience with Databricks: Proficiency with Spark, Delta Lake, and workspace management. - Knowledge of Microsoft Fabric: Experience navigating and implementing solutions within the Fabric ecosystem. - Architecture Design: Solid experience implementing Medallion Architecture. - Data Programming: Proficiency in Python (PySpark) and SQL for data transformation and engineering. Requirements - Cloud Ecosystem: Experience with the Azure platform and Azure Data Factory. - AI Integration: Familiarity with Vector Databases (e.g., ChromaDB) for LLM support. - Power Platform: Experience preparing data for Power BI and Power Apps consumption. - Domain Knowledge: Familiarity with industrial data or engineering calculations. - DevOps for Data: Experience with CI/CD for data pipelines and version control (Git). - Data Governance: Knowledge of data quality standards and metadata management. 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.

• Manage a team by hiring and onboarding talent, setting clear expectations, conducting formal performance reviews, and coaching accountability. • Lead the team to deliver on the enterprise data platform roadmap by translating architecture direction into sequenced execution plans, team backlogs, and measurable outcomes. • Create a strong engineering culture across the team by setting standards for maintainability, organization, and repeatability; growing engineers via regular 1:1s, timely feedback, development plans, and formal review cycles; and being responsible for overall team performance and cohesion. • Own day-to-day execution for the Data Engineering team by breaking work into tasks, driving sprint-level planning, delegating effectively to grow ownership, unblocking delivery, and ensuring high-quality outcomes through engineering reviews and feedback. • Drive implementation of the Medallion architecture (Bronze → Silver → Gold) with strong enforcement of layer responsibilities, ensuring repeatable and auditable pipeline behavior leveraging Boomi, Dbt, Azure Data Bricks, Boomi/Rivery, Delta tables, and Sql Server. • Partner closely with the Data Architect to bring the architecture to life through concrete implementation patterns, reference pipelines, and guardrails—ensuring the team can consistently execute the intended approach. • Reduce friction by driving crisp decisions and forward motion—using lightweight decision records, seeking the right input, and then executing accountability (while avoiding overly heavy process). • Establish DataOps practices aligned with modern software development lifecycle (SDLC): CI/CD for data assets, consistent branching/release patterns, code review standards, and runbooks/operational readiness for pipelines. • Improve pipeline observability and operational reliability by implementing monitoring for freshness/staleness, failure modes, and quality signals, and ensuring the team responds predictably to incidents and support requests. • Drive stakeholder partnership and intake stream: collaborate with business partners to clarify requirements, reduce ad-hoc thrash, and shape requests into deliverable, well-scoped work that fits the platform strategy. • Develop future leaders and succession plans for key roles through assigning regularly occurring responsibilities, mentoring, and strategic delegation. • Support and promote the company values through positive interactions with both internal and external stakeholders on a regular basis. • Other strategic business initiatives or special cross-functional project involvement as required.

• Define and contribute to the evolution of the organization's data architecture strategy • Design scalable and reliable data solutions aligned with business and technical requirements • Evaluate and recommend technologies, frameworks, and architectural standards for data platforms • Collaborate with engineering teams and stakeholders to ensure architecture decisions support business goals • Promote best practices related to data architecture, governance, scalability, and reliability • Support data engineering teams with technical guidance and architectural recommendations • Help identify technical challenges and propose efficient and innovative solutions • Contribute to data security, governance, and compliance standards across data environments • Share knowledge and mentor team members to support their technical development and growth • Participate in discussions related to data strategy, platform evolution, and modernization initiatives • Collaborate with technology partners and vendors when needed