• Plan, manage, and execute releases across all environments - from development to production. • Identify technical and functional interdependencies between various tracks. • Coordinate with all development pods and stakeholders across programs. • Review application code, documentation, and perform pre/post deployment tasks. • Define release process for new data engineering applications. • Change management communication to all required stakeholders. • Execute release packages, step-by-step deployment guides, and command line instructions on production environment. • Support project timelines, clearly setting expectations, and realigning expectations internally as priorities change. • Develop a sound understanding of client’s needs: data conversion and migration requirements, environment management and build processes, deployment planning and execution, solution designs, systems integrations, technical architectures, and infrastructure architectures.

• Lead the design and implementation of the Data Mesh architecture for the Aliare ecosystem; • Define integration strategies between legacy systems and the modern platform; • Establish federated governance standards across domains; • Design multi-cloud architecture (AWS, Azure, GCP); • Lead technical decisions regarding the data lake, APIs, streaming, and orchestration tools; • Mentor the technical team and establish best practices.

Role Description O(a) Engenheiro(a) de Dados deve ser capaz de criar, expandir e otimizar a arquitetura de pipelines de dados, bem como desenvolver e manter fluxos de dados de diversas áreas de nossos clientes. Este(a) profissional deve estar familiarizado(a) com conceitos e estratégias de DataOps, bem como execução de projetos gerenciados em modelo Ágil. O conhecimento de tecnologias de big data é imprescindível para esse cargo. É importante que se relacione bem com diferentes equipes - tecnologia e área de negócio principalmente - e que possa apontar oportunidades de melhoria na forma de estruturação dos dados para atingir o objetivo de análise do cliente. Responsibilities - Criar e realizar manutenção e melhoria de fluxos e dados (ETL e ELT) em casos de alta complexidade - Transformar dados - Realizar desenvolvimento, testagem, homologação, implantação, correção, entrega e automatização de testes em rotinas e processos complexos - Utilizar de ambientes Hadoop, Spark e estruturas Cloud (Azure, AWS e GCP) para construção e execução dos pipelines de dados - Participar de reuniões com equipe e clientes e das cerimônias propostas pela gestão de projetos ágeis - Interagir com áreas de negócio complexas para validação das entregas e realização de possíveis ajustes para o acompanhamento de Engenheiro(a) de Dados intermediários(as) - Identificar oportunidades de melhorias em processos, bem como desenhar e implementar as soluções propostas como: automação de processos manuais, otimização de data delivery, melhoria de arquitetura para aumento de desempenho e outras - Criar e melhorar continuamente a arquitetura de pipelines de dados - Combinar diversas bases de dados grandes e complexas para endereçar requisitos funcionais e não funcionais do negócio Qualifications - Domínio em Databricks - Experiência sólida com linguagem SQL e Python - Conhecimento do stack de dados Azure/AWS/GCP e técnicas de DataOps - Experiência com construção de fluxos de dados utilizando ferramentas de big data - Visão de foco no cliente e habilidade para comunicar ideias de forma clara e concisa, assim como em resolução de problemas Journey to Become a Fiver - Triagem de currículos - Bate-papo com equipe de Gestão Humana - Entrevista Técnica com lideranças do time - Entrevista Final com cliente Benefits - Vales Alimentação e Refeição (Swile) - Flexibilidade para crédito em Auxílio Home-Office (Swile) - Cobertura de até 100% em Plano de Saúde e Odontológico - Seguro de Vida em grupo - Trabalho remoto - Convênio Saúde Mental - psicoterapia online e presencial - Incentivo a certificações e cursos - Convênio para cursos de pós-graduação e MBA (Esalq/USP) - Parceria com escolas de idiomas - Parceria com academias e apps de bem-estar (Wellhub) - Palestras e rodas de conversa internas - Bônus por indicação - Happy hours - Mimos em datas comemorativas

Location: United States (remote) What is Verse? Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical. Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs. The Role You will be a member of the technical staff designing, building, and maintaining the next generation of data platform tools, pipelines, and orchestration frameworks to support multiple teams and products across a diverse range of data at Verse. This role supports Core Engineering needs within the organization and builds on top of existing engineering foundations focused on data. As a technical leader with advanced data engineering expertise, teammates will look to you to vet proposals, solutions to internal and customer-facing problems, system designs, and drive the implementation of these solutions with highest standards of software-engineering best practices. You will be an integral part of scaling our data platform as the company grows. Key Responsibilities - Ensure data quality, contracts and integrity with best practices around access, governance, and federation throughout the data lifecycle - Implement, maintain, and promote best practices and hygiene in our dataland code repository for others to follow and emulate - Write shared libraries and reusable data tools across a variety of data flows, sources, and sinks - Partnering closely with our Data Science and data-heavy internal teams to support various analytical and AI/ML workflows - Foster a culture and mindset of well-designed systems, test-driven software, and proactive communication with a high degree of transparency, mutual respect, and consideration for teammates - Participate in code reviews, maintain technical documentation, and adhere to best software development practices What We're Looking For (Minimum Qualifications) - Advanced software development skills in Python, Rust, Java, Scala, or similar data-oriented language ecosystems - Deep understanding of databases, data {lake,ware}house architectures, and data pipeline solutions across heterogeneous data and workloads in cloud-native environments - Proficiency in carefully handling large, complex data and processing them (streaming and batch) in both transactional and analytical settings - Commitment to delivering high quality software on time or ahead of schedule while adhering to best software development practices - Continuous obsession for staying informed on contemporary technologies, tools, libraries, services, frameworks, or breakthroughs that could benefit the team - Discipline using generative AI tools in day-to-day work What Will Make You Standout (Preferred Qualifications) - Bachelor’s or master's degree in Computer Science, Data Science, or a related field - Senior level software development talent and up - Proven track record being a technical leader in high-performing data engineering teams - Intimate knowledge of scaling “big data” solutions in cloud-based environments - Hands on experience deploying and maintaining software such as Hadoop, Spark, Airflow, DBT, Dagster, Temporal, Presto/Trino, Iceberg, AlloyDB, Postgres, HBase, BigQuery, BigTable, Fabric, Hive, RedShift, S3, GCS, etc. - Experience building event-driven architectures with streaming tools such as Kafka, NATS, GCP Pub/Sub, Kinesis, Bufstream, Flink, Beam - Knowledge of managed or hosted data solutions such as Databricks, Snowflake, ClickHouse, Tinybird, etc - Practical knowledge working with data in formats like Parquet, Avro, Protobuf, time series, text, image, video - Working closely to support AI/ML-focused teams (knowledge of MLflow and Ray is a big a plus) - Comfort building internal dashboards and data-focused visualizations What Makes Verse a Great Place to Work? - Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first - Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders - Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection - Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations Base Pay Range $180,000 - $250,000+ This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to level, skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. Benefits and Employee Perks - Competitive compensation and equity grant at a high-growth start up - Comprehensive benefits package including medical, dental and vision insurance, and 401k - Flexible hours and unlimited PTO - Diverse and inclusive working environment Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.