Data Engineer Sr

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Valtech

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

Fundada em 1997

🤝 B2B

☁️ SaaS

B2B • Marketing • SaaS

Valtech é uma agência digital global focada em inovação em experiências. A empresa se dedica a transformar negócios por meio da combinação de tecnologia, marketing e estratégias orientadas por dados. A Valtech ajuda companhias a elevar sua presença digital e impulsionar estratégias de Commerce, a acelerar transformações digitais em nível corporativo e a destravar o potencial de marketing e performance. A empresa também utiliza dados e IA para ajudar organizações a aproveitar o poder da informação. Com escritórios ao redor do mundo, a Valtech faz parcerias com empresas para moldar seus futuros digitais, oferecendo um conjunto de serviços e insights projetados para aprimorar as experiências dos clientes.

Descrição

• Lead complex data engineering workstreams across multiple business areas, source systems, domains, or stakeholder groups. • Define data engineering approaches that align business needs, source-system realities, platform constraints, transformation patterns, and downstream consumption requirements. • Translate ambiguous stakeholder needs into structured pipeline strategies, ingestion patterns, transformation designs, curated data layers, and actionable recommendations. • Guide the design and implementation of scalable ingestion, transformation, and serving patterns across cloud warehouses, lakehouses, and analytical environments. • Establish and reinforce best practices for schema design, pipeline modularity, layered data architecture, data validation, lineage awareness, scheduling discipline, error handling, and maintainable engineering patterns. • Design and improve reusable data engineering workflows that support reporting, dashboarding, data science, AI workflows, and agentic use cases. • Support team staffing, work allocation, prioritization, and delivery quality across data engineering engagements. • Manage, coach, and develop practitioners through feedback, guidance, and performance support. • Review deliverables for clarity, technical rigor, quality, consistency, and business usefulness. • Help teams improve data quality, reduce pipeline fragility, strengthen source alignment, and increase trust in downstream governed datasets. • Support data engineering patterns that improve AI and agentic readiness, including metadata-rich datasets, retrieval-supportive organization, document and chunk preparation support, governed access paths, and scalable data availability for downstream workflows. • Collaborate with Analytics Engineers, Data Analysts, Data Scientists, AI Scientists, AI Engineers, AI Platform Engineers, and Architects to align data foundations with downstream analytical, AI, and platform needs. • Contribute to hiring, onboarding, capability development, and team maturity within the data engineering practice. • Follow established governance, privacy, security, and data-quality standards across the work of the team.

🎯 Requisitos

• +5 years of experience in data engineering • Deep working knowledge of data engineering, cloud-based data platforms, and scalable pipeline design • Strong ability to define data engineering approaches in complex business environments with multiple systems, domains, and downstream consumers • Strong people leadership skills, including coaching, feedback, prioritization, and support for team development • Strong understanding of ETL and ELT concepts, schema evolution, orchestration, dependency management, layered data design, and downstream data consumption needs • Strong familiarity with SQL, Python, Spark, PySpark, and cloud-native data engineering workflows • Strong understanding of medallion, lakehouse, warehouse, or layered architectural patterns and their role in governed data reuse • Strong analytical and problem-solving skills across data-quality issues, performance challenges, dependency risks, and transformation design • Working understanding of how reliable data foundations enable machine learning, AI workflows, retrieval quality, agentic systems, and governed application behavior • Strong stakeholder management skills and the ability to communicate clearly with technical and non-technical audiences • Ability to balance delivery quality, team workload, business urgency, and stakeholder expectations across multiple workstreams • Strong written and verbal communication skills in English, including confidence in client-facing and leadership-facing settings • Ability to collaborate effectively across distributed teams in the Americas and across multiple disciplines • Upper-intermediate English level • Technical Requirements: Microsoft Fabric, Microsoft Foundry, APIM Gateway, App Insights, and Cosmos DB

🏖️ Benefícios

• Flexibility, with remote and hybrid work options (country-dependent) • Career advancement, with international mobility and professional development programs • Learning and development, with access to cutting-edge tools, training and industry experts