Lead Software Engineer

Emploi pas sur LinkedIn

🕒 il y a 10 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

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Empower

Site WebLinkedInTous les Emplois

10 000+ employés

💸 Finance

💳 Fintech

👥 B2C

Finance • Fintech • B2C

Empower est un prestataire de services financiers de premier plan, axé sur l'aide aux individus et aux organisations pour atteindre la liberté financière grâce à la planification de la retraite et à la gestion des investissements. Au service de plus de 19 millions d'Américains, Empower propose une suite complète de services liés aux finances, incluant la planification intelligente, les conseils en investissement, et des outils comme le tableau de bord personnel Empower™ pour une vue d'ensemble financière. L'entreprise est réputée en tant que principal fournisseur de plans de retraite et collabore étroitement avec des investisseurs individuels, des épargnants sur le lieu de travail, des promoteurs de plans et des professionnels financiers. Empower est également reconnu pour ses initiatives en matière de diversité, d'équité, d'inclusion et a un engagement social qui renforce l'impact communautaire.

Description

• 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

🎯 Exigences

• 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.

🏖️ Avantages

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