Lead Software Engineer

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🕒 Maio 28

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

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Empower

SiteLinkedInTodas as Vagas

10.000+ funcionários

💸 Finanças

💳 Fintech

👥 B2C

Finance • Fintech • B2C

A Empower é uma fornecedora líder de serviços financeiros focada em ajudar indivíduos e organizações a alcançar a liberdade financeira através do planejamento de aposentadoria e da gestão de investimentos. Atendendo a mais de 19 milhões de americanos, a Empower oferece um conjunto abrangente de serviços relacionados a finanças, incluindo planejamento inteligente e aconselhamento de investimento, além de ferramentas como o Empower Personal Dashboard™ para uma visão financeira completa. A empresa é renomada como uma das principais provedoras de planos de aposentadoria e trabalha de perto com investidores pessoais, poupadores de planos no local de trabalho, patrocinadores de planos e profissionais financeiros. A Empower também é reconhecida por suas iniciativas em Diversidade, Equidade, Inclusão e tem um compromisso social que fortalece o impacto na comunidade.

Descrição

• Play a critical role across the full data lifecycle—from business requirements gathering and data modeling to solution architecture, development, deployment, and production support • Lead the design and implementation of high-performance data pipelines, real-time streaming architectures, and analytics-ready data models while driving innovation through GenAI-enabled data solutions • Design, develop, and implement scalable batch and real-time data pipelines using Snowflake, Amazon Redshift, and AWS-native technologies • Lead end-to-end data engineering initiatives including data ingestion, transformation (ETL/ELT), data quality, and data delivery across enterprise platforms • Build and optimize cloud-native data solutions leveraging AWS services such as S3, Lambda, Glue, ECS, EMR, IAM, CloudWatch, and related services • Develop and maintain modern ELT transformation frameworks using dbt (Data Build Tool) for modular, testable, and scalable data modeling • Implement and support real-time and CDC-based streaming architectures using tools such as Kafka, STRIIM, and event-driven integration frameworks • Collaborate with data architects, analysts, product owners, and business stakeholders to gather requirements and translate them into technical solutions • Drive best practices in data modeling, governance, metadata management, lineage, and performance optimization • Implement observability and monitoring solutions using tools such as Datadog, CloudWatch, and custom alerting frameworks to ensure platform reliability and operational excellence • Lead code reviews, establish engineering standards, and champion CI/CD and DevOps practices for data platforms • Troubleshoot and resolve complex production issues related to data pipelines, orchestration, and warehouse performance • Mentor junior and mid-level engineers, fostering a culture of technical excellence and continuous learning • Evaluate and adopt emerging technologies in cloud, AI/ML, and data engineering to drive innovation across the organization • Enable AI/ML initiatives by building trusted, scalable, and high-quality datasets for advanced analytics and GenAI applications • Partner with cross-functional teams to implement secure, compliant, and highly available enterprise data solutions

🎯 Requisitos

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field • 12+ years of experience in Data Engineering, Data Warehousing, and Software Development • Strong expertise in SQL and Python with experience building enterprise-scale data solutions • Hands-on experience with Snowflake and Amazon Redshift in large-scale production environments • Strong experience with modern data transformation frameworks such as dbt • Experience with orchestration and workflow tools such as Apache Airflow • Hands-on experience with streaming and CDC technologies such as Kafka, STRIIM, or similar event-streaming platforms • Experience building and supporting observability frameworks using Datadog or equivalent monitoring platforms • Familiarity with Vector Databases and AI/GenAI integration patterns for intelligent data applications • Exposure to GenAI tools, LLM-powered workflows, or AI-enabled analytics platforms is highly preferred • Strong understanding of dimensional and normalized data modeling techniques • Experience working with AWS cloud services including S3, Lambda, Glue, IAM, ECS, CloudFormation, and related technologies • Knowledge of CI/CD implementation using tools such as GitHub Actions, Jenkins, Terraform, or similar platforms • Experience with data governance, data quality frameworks, and security best practices • Excellent problem-solving, analytical, and communication skills • Proven ability to lead technical initiatives and mentor engineering teams • Passion for innovation, continuous learning, and adopting modern data engineering practices.

🏖️ Benefícios

• flexible work environment • internal mobility • purpose and well-being • work-life balance • inclusive environment • volunteering opportunities