Forward Deployed Data Engineer IV, Databricks

🕒 Setembro 16

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $175.000 - $200.000 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 4%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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E Source

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 1986

⚡ Energia

💼 Consultoria

🤝 B2B

Energy • Consulting • B2B

A E Source é uma empresa de pesquisa, ciência de dados e consultoria que auxilia concessionárias de eletricidade, gás e água a tomar e implementar decisões baseadas em dados. A empresa combina pesquisa líder do setor, benchmarking, serviços de consultoria e análises aplicadas (incluindo suporte de machine learning e IA) para melhorar a experiência do cliente, otimizar operações de rede, modernizar processos de negócios e de campo, e projetar e avaliar programas de energia. A E Source oferece soluções em operações de clientes, estratégia e medição de DER, planejamento e implementação de AMI, inteligência de vegetação/ tempestades/incêndios/florestais/ confiabilidade, estudos de interconexão, estratégia e governança de dados, e transformação da força de trabalho e tecnologia. Atende concessionárias em toda a América do Norte e enfatiza a ligação entre estratégia e execução para resultados operacionais e de clientes mensuráveis.

Descrição

• Embed with utility clients to design and build production data platforms end to end • Build ingestion, transformation, orchestration, quality, governance, and serving systems using Databricks, Spark, Python, SQL, and AWS • Own technical architecture for each engagement and defend it to client architects, security teams, and platform owners • Conduct independent technical discovery and identify underlying client needs • Deliver a working system within the first few weeks and iterate toward production hardening • Lead migrations from legacy warehouses and on-premises systems to modern platforms • Model data using dimensional, lakehouse/medallion, graph, or semantic models as appropriate • Integrate utility source systems including asset and work management, historians/SCADA, CIS, AMI, GIS, and ERP • Make pipelines observable and operable through lineage, quality checks, alerting, and runbooks • Build and deploy operator-facing application layers such as data quality dashboards, reconciliation interfaces, and self-service data tools • Manage scope, timeline, expectations, risks, and measurable outcomes against statements of work • Contribute reusable frameworks, ingestion patterns, and reference architectures • Provide product and implementation feedback to E Source engineering and product teams • Apply governance, security, privacy, and retention controls appropriate to utility regulations • Work with client data/IT teams, executives, and E Source ML engineers, software engineers, data scientists, and consultants • Travel to client sites approximately 30–50%, varying by engagement, including extended on-site periods

🎯 Requisitos

• Bachelor’s degree in computer science, information technology, or a related field • Five or more years of experience in data engineering, data platform, or analytics engineering • At least one platform owned in production • Expert proficiency in Python, SQL, Databricks, and Spark, including Spark runtime internals • Ability to diagnose why a Spark job is slow rather than simply adding compute • Experience building cloud-based data pipelines in AWS • Working knowledge of a second cloud ecosystem preferred • Experience with incremental versus full rebuild, idempotency, late-arriving data, deduplication, backfill strategy, and schema evolution • Batch and streaming pipeline design experience • Knowledge of data governance, security, privacy, lineage, and quality practices • Proficiency with Git, Docker, CI/CD tools, and at least one modern orchestration framework • Demonstrated experience using AI coding assistants and agentic development tools • Experience in the energy or utility industry, or another asset-heavy sector • Strong written communication and whiteboarding skills • Master’s degree in a relevant STEM field preferred • Graph database and knowledge graph modeling experience preferred • Production experience with Kafka or equivalent streaming platforms and change data capture tooling preferred • Experience building feature pipelines and serving data to ML and AI systems preferred • Experience building and deploying Databricks Apps or comparable operator-facing applications preferred • Experience with React, Streamlit, or Dash and REST or GraphQL APIs preferred • Experience optimizing Databricks cost and performance preferred • Databricks certification preferred • Applicants must be authorized to work for any employer in the US • Employment visa sponsorship is unavailable

🏖️ Benefícios

• Excellent insurance options, including medical, dental, and vision plans • Company-paid life insurance • Company-paid long- and short-term disability insurance • Medical and dependent-care flexible spending plans • Paid parental leave • Flexible time off (FTO) policy • 401(k) plan with a 3% employer match • Annual bonus • Remote-based work within the US • Significant travel to client sites, including extended on-site periods during discovery, deployment, and go-live