Dadosfera

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, and AWS services • Design and evolve layered Data Lake architectures following the Medallion Architecture pattern • Build solutions for ingesting, processing, and integrating structured, semi-structured, and unstructured data • Apply Artificial Intelligence, Machine Learning, or Large Language Models (LLMs) to classify, standardize, validate, and enrich data • Collaborate with software engineers, data analysts, business stakeholders, and clients to translate business requirements into scalable technical solutions

• Desenvolver e manter camadas analíticas focadas no consumo de negócios • Traduzir necessidades de negócios em modelos de dados escaláveis e reutilizáveis • Garantir qualidade, documentação e governança de ativos analíticos • Colaborar com Engenheiros de Dados para evoluir pipelines e conjuntos de dados • Construir métricas corporativas e camadas semânticas para consumo em Power BI e Metabase • Apoiar iniciativas de Self-Service Analytics • Participar da definição e adoção de catálogos de dados e documentação técnica • Atuar como um elo entre equipes técnicas e partes interessadas de negócios

• Desenvolver e manter pipelines de dados usando Apache Spark e Apache Airflow • Construir e melhorar integrações entre diferentes fontes de dados corporativas • Implementar transformações de dados seguindo as melhores práticas de engenharia e padrões de observabilidade • Suportar a manutenção e otimização de ambientes que rodam em containers e Kubernetes • Suportar o desenvolvimento e manutenção de modelos analíticos utilizados pelo Power BI e Metabase. • Colaborar com Engenheiros de Análise para fornecer ativos de dados confiáveis e bem documentados para equipes de negócios. • Contribuir para iniciativas de catalogação de dados, documentação e governança de dados. • Participar da evolução de agentes de AI utilizados pela equipe de Dados.

• Support the creation and publication of content for social media, blogs, and other communication channels. • Assist in planning and executing digital marketing campaigns. • Help produce institutional and promotional materials. • Monitor performance metrics and prepare basic reports. • Conduct market, competitor, and industry trend research. • Use Artificial Intelligence (AI) tools to support content creation, information analysis, and process optimization. • Collaborate with different teams on communication and marketing initiatives.

• Support the creation of demos and exploratory analyses using SQL and data analysis tools • Assist in developing queries, reports, and visualizations to support projects • Perform technical tasks such as environment setup, task automation, and cloud infrastructure support under the guidance of the technical team • Collaborate in building prototypes and proofs of concept using real-world datasets • Support technical community initiatives, events, training sessions, and content-creation activities.

• Identify, develop, and convert new business opportunities, acting in both Hunter and Farmer roles; • Manage mid-market and enterprise accounts, developing commercial strategies aligned with Dadosfera’s business goals; • Understand clients’ challenges, needs, and objectives, connecting them with the most suitable Dadosfera products, solutions, and services; • Conduct commercial meetings, institutional presentations, solution demonstrations, and negotiations with national and international clients; • Build and maintain strong client relationships, ensuring proximity, trust, and a long-term partnership vision; • Keep commercial activities updated in the CRM, ensuring visibility, predictability, and accurate sales pipeline tracking; • Collaborate closely with Dadosfera’s technical teams to structure solutions tailored to each client’s context and challenges; • Support the development of commercial proposals, business cases, and account growth strategies.

• Support outbound prospecting activities via email, LinkedIn, phone calls, and other prospecting channels • Make initial contact with cold leads and assist in qualifying leads based on Dadosfera's ideal customer profile • Support inbound lead qualification activities • Assist in building and executing prospecting cadences • Identify business opportunities and support scheduling meetings for the sales team • Keep the CRM updated with contact information, interactions, and opportunity status • Support the organization of prospecting lists and conduct research on companies and decision-makers • Collaborate with Sales and Marketing teams to improve outreach strategies, messaging, and commercial campaigns • Track prospecting metrics such as outreach volume, response rates, and meetings scheduled • Learn and apply best practices in sales communication, lead qualification, and consultative selling.

• Conduct active outbound prospecting via phone calls, email, LinkedIn, and other outbound channels; • Reach out to cold leads and support lead qualification activities according to the company's ideal customer profile; • Assist with initial outreach strategies to generate interest and schedule meetings for the sales team; • Keep CRM systems up to date with contact information, interaction history, and opportunity status; • Support prospecting routines, sales cadences, and contact processes; • Monitor outreach activities and performance metrics such as contact volume and meetings scheduled; • Collaborate with Sales and Marketing teams to improve prospecting messages and approaches; • Handle objections and high-volume outreach activities with organization and resilience.

• Lead client projects, ensuring high data quality. • Develop, maintain, and improve data pipelines. • Evolve cloud platforms and solutions using expertise in Cloud, DataOps, and Data Engineering. • Contribute to architectural decisions, mitigation of technical debt, and agile practices. • Participate in internal training and alignment activities at Dadosfera.

• Assist with extracting, cleaning, and preparing datasets for analysis. • Contribute to the development of basic reports and data visualizations for internal stakeholders and clients. • Analyze patterns and trends in data, supporting the use of statistical models and machine learning. • Collaborate with business teams to provide actionable insights. • Support the identification of data quality issues and assist in their resolution.