Lead Software Engineer

Job not on LinkedIn

🕒 6 days ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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Empower

WebsiteLinkedInAll Job Openings

10,000+ employees

💸 Finance

💳 Fintech

👥 B2C

Finance • Fintech • B2C

Empower is a leading provider of financial services focused on helping individuals and organizations achieve financial freedom through retirement planning and investment management. Serving over 19 million Americans, Empower offers a comprehensive suite of finance-related services, including smart planning and investment advice, and tools like the Empower Personal Dashboard™ for a complete financial view. The company is renowned as a top retirement plan provider and works closely with personal investors, workplace plan savers, plan sponsors, and financial professionals. Empower is also recognized for initiatives in Diversity, Equity, Inclusion, and has a social commitment that bolsters community impact.

📋 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

🎯 Requirements

• 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.

🏖️ Benefits

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