Senior Data Engineer – Data Platform

🕒 Julho 11

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 17%

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SunStrong Management

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2024

⚡ Energia

🤝 B2B

🔥 Investimento no último ano

💰 $900.000.000 Debt financing em 2025-11

Energy • B2B

A SunStrong Management é uma empresa de gestão de operações e ativos que gerencia infraestrutura de energia e solar distribuída em nome de proprietários, investidores institucionais e clientes residenciais. A empresa se especializa em operações e manutenção (O&M) de serviços de campo, faturamento e cobranças, e engajamento e relatórios para investidores, frequentemente intervindo para administrar ativos solares abandonados por originadores para manter os sistemas em funcionamento e os clientes atendidos. A SunStrong conecta parceiros de capital com foco em sustentabilidade e operações de infraestrutura do mundo real para entregar um desempenho de confiança e retornos estáveis aos investidores.

Descrição

• Design, build, and operate end-to-end data pipelines (batch and near-real-time) that ingest, transform, and deliver data from diverse sources into the enterprise data platform. • Develop and maintain curated data models, marts, and shared datasets in Snowflake and PostgreSQL that meet performance, quality, and access-control requirements for multiple internal customers. • Implement data quality frameworks including automated validation, schema enforcement, reconciliation checks, duplicate detection, and exception reporting with clear audit trails. • Partner with domain teams (e.g., Asset Management, Finance, Operations) to understand data needs, define contracts and SLAs, and deliver platform capabilities that reduce bespoke engineering and manual effort. • Build parameterized, reusable pipeline components and templates that standardize ingestion patterns, transformations, and deployment across the platform. • Establish and maintain data lineage, metadata, and documentation so stakeholders can trace data from source to consumption with confidence. • Collaborate with IT and security to implement role-based access controls, data masking, encryption, and compliance requirements across platform resources. • Own pipeline orchestration, scheduling, dependency management, and alerting using workflow tools (e.g., Airflow) to ensure reliable, recoverable execution. • Improve platform observability through logging, metrics, SLA monitoring, and incident response practices that minimize downtime and data freshness gaps. • Support CI/CD and infrastructure-as-code practices for data platform assets, including version control, automated testing, and safe promotion across environments. • Evaluate and integrate new platform technologies and patterns (e.g., streaming, CDC, data mesh principles) where they improve scalability, cost efficiency, or time-to-value. • Mentor junior engineers and contribute to platform standards, code review practices, and technical design documentation.

🎯 Requisitos

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field. • 5+ years of experience in data engineering or platform engineering, preferably in a financial services or regulated industry (e.g., asset management, banking, insurance, fintech). • Strong SQL and Python skills, with a track record of building production-quality data pipelines, transformations, and validation frameworks. • Proficient at using AI-assisted development tools to design, build, and iterate on data pipelines while maintaining code quality, security, and governance standards. • Hands-on experience with Snowflake and PostgreSQL, including performance tuning, cost optimization, and secure multi-tenant data access patterns. • Experience with pipeline orchestration and workflow management tools (e.g., Apache, Airflow, Dagster, or equivalent). • Proficiency with Git, code review, and CI/CD practices for data platform development. • Experience designing dimensional or domain-oriented data models and delivering curated datasets for analytics and operational use cases. • Familiarity with data quality, lineage, and governance tooling and practices (preferred). • Experience with cloud data services (e.g., AWS, Azure, or GCP) and infrastructure-as-code (e.g., Terraform) is strongly preferred. • Exposure to streaming or change-data-capture (CDC) patterns and event-driven architectures is a plus. • Understanding of financial data domains (e.g., portfolio, investor reporting, accounting) is helpful but not required; curiosity and ability to partner with domain experts is essential. • Strong communication and collaboration skills; ability to translate ambiguous requirements into well-scoped technical designs and clear status reporting. • Familiarity with containerization (e.g., Docker/Kubernetes) and API/integration patterns for data services is a plus.

🏖️ Benefícios

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development