Role Description Staritas is seeking a Senior Manager of Data Engineering to lead its enterprise data engineering function, including data platform strategy, roadmap execution, modernization, production operations, data quality, governance, and team development. This role is ideal for a hands-on data leader who can scale modern data platforms, improve reliability, guide technical standards, and partner across Technology, Product, Analytics, Security, Operations, and business teams to deliver trusted, secure, and business-ready data capabilities. - Lead and develop a high-performing data engineering team. - Own the data engineering roadmap, delivery planning, technical standards, and platform reliability. - Partner with the CTO and technology leaders on data strategy, modernization, architecture, governance, and operating model. - Deliver scalable ELT/ETL pipelines, data warehouses, data lakes, marts, semantic layers, curated datasets, and analytical data products. - Establish standards for data modeling, orchestration, testing, documentation, code review, CI/CD, monitoring, and production support. - Improve data quality, observability, lineage, alerting, incident response, and DataOps practices. - Reduce technical debt, duplicated datasets, manual reporting, fragile integrations, and recurring production issues. - Support AI, machine learning, advanced analytics, and self-service analytics with trusted, governed, and secure data foundations. - Promote a culture of ownership, accountability, collaboration, documentation, and continuous improvement. Qualifications - Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Engineering, Mathematics, or related field; equivalent experience considered. - 10+ years of technology experience, including data engineering, data architecture, analytics engineering, integration, or enterprise data platform delivery. - 5+ years leading data engineers, analytics engineers, architects, technical leads, or similar teams. - Proven experience delivering enterprise data platforms, production data operations, technical standards, and stakeholder-facing roadmaps. - Strong experience with cloud data platforms, data warehouses, data lakes/lakehouses, data marts, APIs, integrations, and production support. - Hands-on experience building ELT/ETL pipelines. - Experience with Informatica or comparable enterprise data integration platforms. - Strong SQL skills and experience with relational, NoSQL, columnar, and analytical databases. - Experience with AWS, Azure, Google Cloud, or hybrid cloud environments. - Knowledge of orchestration, transformation, data modeling, CI/CD, testing, observability, documentation, agile delivery, governance, metadata, lineage, data quality, and secure access. Preferred Qualifications - Experience with Informatica IDMC, PowerCenter, Data Quality, or Cloud Data Integration. - Familiarity with tools such as Spark, PySpark, Airflow, dbt, Databricks, Snowflake, BigQuery, Redshift, Azure Data Factory, AWS Glue, Power BI, GitHub, GitLab, Jira, or Confluence. - Experience modernizing legacy ETL, fragmented data ecosystems, and manual reporting processes. - Experience supporting AI, machine learning, predictive analytics, or advanced analytics use cases. - Experience in regulated, compliance-oriented, SaaS, ERP, CRM, healthcare, financial, or analytics environments. Requirements - Reliable delivery of the data engineering roadmap. - Improved platform reliability, performance, security, observability, and production support. - Reduced data quality issues, manual work, duplicated datasets, and recurring defects. - Clear and adopted data definitions, lineage, documentation, governance, and access patterns. - Trusted data foundations that support analytics, reporting, operations, product intelligence, and AI. - An engaged, accountable, and growing data engineering team. Benefits - Competitive salary and performance bonus program. - Fully remote work environment. - Comprehensive benefits package including 401k match. - 19 days of PTO per year; 10 holidays per year. - Opportunity to work in a mission-driven organization where your work directly shapes clarity, confidence, and better outcomes across healthcare. - Up to 10% travel, based on business needs.

Role Description Na Qualificar TI, somos especialistas em Governança de Dados, Gerenciamento de Projetos, Transformação Digital e Outsourcing. Se você gosta de aprender, compartilhar conhecimento e construir soluções que fazem diferença, esta vaga é para você. - Elaboração, implantação e condução técnica de projetos de redes WAN, LAN e WLAN. Qualifications - Formação: Bacharelado nas áreas de Tecnologia de Informação. - Experiência consolidada com especificação e implantação de redes WAN, LAN e WLAN, comprovado em carteira ou carta/declaração de empregador anterior. Requirements - Certificações obrigatórias: - Certified Data Management Professional (CDMP) da DAMA International. - Certified Information Management Professional (CIMP) da eLearningCurve. - Pós-graduação ou MBA em Gestão da Informação, Gestão de Dados, ou Governança de TI. Benefits - Ambiente Inovador: Aqui você trabalha com um time diverso e colaborativo, que valoriza o seu conhecimento e incentiva seu crescimento. - Desenvolvimento Contínuo: Oferecemos treinamentos, certificações e programas de capacitação para você evoluir sempre. - Impacto Real: Atuamos em projetos estratégicos que transformam empresas e entregam resultados concretos. - Cultura que acolhe: Valorizamos a diversidade como parte da nossa cultura e acreditamos que a inovação nasce das diferenças.

Role Description Responsável por coletar, organizar, processar e analisar grandes volumes de dados. Ele desempenha um papel crucial na construção e manutenção de infraestruturas e arquiteturas de dados, garantindo que as informações sejam acessíveis, seguras e prontas para análise. - Desenvolver pipelines de dados para ingestão, limpeza, transformação e armazenamento de dados. - Colaborar com cientistas de dados e analistas para garantir que os dados sejam utilizados de forma eficaz na geração de insights e na tomada de decisões estratégicas. Qualifications - Diploma de bacharelado em Ciência da Computação, Engenharia de Software, Sistemas de Informação, Tecnologia da Informação ou áreas afins. - Experiência prática consolidada em projetos de dados, desenvolvendo soluções ETL, modelagem de dados, e colaborando com cientistas de dados e analistas. - Certificações obrigatórias: - Certified Data Management Professional (CDMP) da DAMA International. - Certified Information Management Professional (CIMP) da eLearningCurve. - Pós-graduação ou MBA em Gestão da Informação, Gestão de Dados, ou Governança de TI. Requirements - Não se aplica. Benefits - Ambiente Inovador: Aqui você trabalha com um time diverso e colaborativo, que valoriza o seu conhecimento e incentiva seu crescimento. - Desenvolvimento Contínuo: Oferecemos treinamentos, certificações e programas de capacitação para você evoluir sempre. - Impacto Real: Atuamos em projetos estratégicos que transformam empresas e entregam resultados concretos. - Cultura que acolhe: Valorizamos a diversidade como parte da nossa cultura e acreditamos que a inovação nasce das diferenças.

Role Description The Data Engineer is a critical member of a small, high-performing data team. This person is responsible for the full data journey — from source systems through to the semantic data layer that powers analytics across the organization. They work closely with domain-partnered analysts to ensure data is structured, reliable, and genuinely useful for the business questions it needs to answer. The right person starts from business context and works toward technical solutions — independently translating ambiguous requests into well-formed data that makes the business legible. They are as comfortable talking to a stakeholder about what a metric means as they are optimizing a Snowflake query. What you'll do - Work with stakeholders and analysts to understand how the business operates and translate that understanding into well-structured, consistent data models. - Ensure data models reflect business processes and terminology — not just technical schema. - Extend and evolve the data model in a consistent, forward-looking manner that preserves coherent patterns across the platform. - Set and uphold the standard for how data is engineered from source to core layer — the craft, the patterns, and the business logic translation; be opinionated about how things get built, not just whether they work. - Work collaboratively across the full data stack with domain-partnered analysts; the DE takes the lead source-side, analysts take the lead consumption-side, and both contribute across the full stack as needed — accountability naturally increases with proximity to your area of the stack. Qualifications - 5+ years of experience in data engineering, analytics engineering, or a closely related field. - Proven track record of building and maintaining data models that are used and trusted by analysts and business stakeholders. - Strong SQL skills; able to write, optimize, and review complex transformation logic. - Strong Python skills; able to work confidently across pipeline logic, scripting, and infrastructure-as-code in a production environment. - Hands-on experience with dbt (Core or Cloud) in a production environment. - Experience with Snowflake as a data warehouse platform. - Practical AWS data engineering experience (e.g., S3, Lambda, Glue, Step Functions, or similar). - Solid understanding of ELT patterns, data modelling concepts (including dimensional modelling), and data testing approaches. - Proficiency with core development tooling: Git, GitHub, CI/CD pipelines, linters. - Familiarity with workflow orchestration and scheduling concepts. - Experience building or contributing to semantic layers for BI tools. - Experience with Airflow or comparable orchestration tooling. - Snowflake cost management and query/compute optimization experience. - Experience with data governance frameworks and practices. - Demonstrated, practical use of AI-assisted development tools (e.g., Claude Code, GitHub Copilot) embedded into daily engineering workflow — active use, not just awareness. Non-technical Requirements - Demonstrated ability to work independently in a self-directed environment without requiring day-to-day task assignment from a Scrum Master or team lead. - Proven experience navigating ambiguous business and technical challenges, with the initiative to identify, engage, and collaborate with the appropriate stakeholders to gather, define, and refine project requirements. - Strong stakeholder management and communication skills, with the ability to translate business needs into actionable technical solutions. - Solid experience in solution architecture, data modeling, and data warehouse design, with a strong understanding of scalable and maintainable data solutions. - Ability to conceptualize, design, and implement effective solutions for complex or loosely defined business problems. - Strong technical execution skills combined with architectural thinking to support end-to-end data engineering and analytics initiatives. Our Hiring Process We utilize AI tools to enhance hiring efficiency and ensure a fair evaluation. Consequently, candidates will engage with an AI Interviewer, supervised by Human Talent Acquisition Experts who will support your entire application journey. While we encourage you to use AI for CV refinement and research, we require that all interviews and assessments be completed through your own authentic effort. The use of real-time AI assistance during interviews or to complete skills tests is strictly prohibited to ensure a fair and genuine evaluation of your capabilities. Benefits - Meaningful work & Growth: We take every opportunity to stretch ourselves and deliver an excellent client experience. - Employee as our biggest asset: We are genuinely invested in our people’s career and welfare. - Global reach & local impact: Get to work with high-growth startups and dynamic companies from the comfort of your own home. - Powering global startups: We’ve created 1,400 Filipino jobs that empower global start-ups to focus on growth.