Senior Data Engineer - Enterprise Data Management

Voya Financial • Hartford, CT

17d

About The Position

Together we fight for everyone’s opportunity for a better financial future. We will do this together — with customers, partners and colleagues. We will fight for others, not against: We will stand up for and champion everyone’s access to opportunities. The status quo is not good enough … we believe every individual and every community deserves access to financial opportunities. We are determined to support both individuals and communities in reaching a better financial future. We know that reaching this future depends on our actions today. Like our Purpose Statement, Voya believes in being bold and committed to action. We are committed to a work environment where the differences that we are born with — and those we acquire throughout our lives — are understood, valued and intentionally pursued. We believe that our employees own our culture and have a responsibility to foster an environment where we all feel comfortable bringing our whole selves to work. Purposefully bringing our differences together to positively influence our culture, serve our clients and enrich our communities is essential to our vision. Are you ready to join a company with a strong purpose and a winning culture? Start your Voyage – Profile Summary: The Senior Data Engineer, leads the design and implementation of robust data solutions across multiple domains, driving technical excellence and scalability. This role mentor others, shape best practices, and influence data architecture. This role is expected to proactively identify opportunities to improve systems, drive reliability, and collaborate with product and business stakeholder to again data strategy and company goals. Profile Description: Design, build and scale robust, high-performing batch and real-time data pipelines. Drive architectural decisions for transformation logic, storage formats, and schema design. Lead complex data ingestion efforts and mentor peers on performance optimization and scalability. Lead the design and optimization of complex data models and storage architecture, balancing performance, scalability, and usability. Partner with stakeholders to translate business requirements into robust data structures. Contribute significantly to delivery planning and execution, mentor junior engineers on agile approaches, and ensure timely completion of tasks by managing dependencies and escalating delivery challenges. Design and standardize advanced data validation frameworks and testing strategies across platforms. Lead root cause analysis and data quality issues and mentor others on quality best practices. Partner with stakeholders to define SLAs and quality metrics. Leads efforts to automate, monitor, and scale deployment of production-grade data pipelines. Design resilient workflows with retry logic, failure handling, and resource optimization. Proactively address performance and reliability issues and contribute to runbooks and on-call documentation. Lead the creation and maintenance of detailed technical documentation for complex pipelines, data models, and system integrations. establish and enforce documentation and development standards across projects. Mentor junior engineers on clear, consistent coding and documentation habits. Act as a key technical partner to product, analytics and data science teams. Lead design, discussions, communicate complex data trade-offs with clarity, and proactively surface risks and blockers. Support collaborative planning and mentor junior team members in effective communication and partnership.

Requirements

• 5-9 years in data engineering, data modeling, and pipeline development
• Expert in SQL and Python for developing and debugging scalable data pipelines.
• Deep hands-on experience with Azure and Databricks, including Delta Live Tables and Unity Catalog
• Skilled with data integration/orchestration tools (SnapLogic, Azure Data Factory, Jenkins)
• Strong use of infrastructure-as-code tools like Terraform to manage deployment pipelines.
• Design and optimize API integration in pipelines.
• Familiar with data quality observability tools such as Soda or similar.
• Proficient in version control and CI/CD workflows using GitHub.
• Advanced understanding of dimensional modeling and data warehousing concepts.
• Comfortable leading efforts in agile environments and strong ownership and collaboration.

Responsibilities

• Design, build and scale robust, high-performing batch and real-time data pipelines.
• Drive architectural decisions for transformation logic, storage formats, and schema design.
• Lead complex data ingestion efforts and mentor peers on performance optimization and scalability.
• Lead the design and optimization of complex data models and storage architecture, balancing performance, scalability, and usability.
• Partner with stakeholders to translate business requirements into robust data structures.
• Contribute significantly to delivery planning and execution, mentor junior engineers on agile approaches, and ensure timely completion of tasks by managing dependencies and escalating delivery challenges.
• Design and standardize advanced data validation frameworks and testing strategies across platforms.
• Lead root cause analysis and data quality issues and mentor others on quality best practices.
• Partner with stakeholders to define SLAs and quality metrics.
• Leads efforts to automate, monitor, and scale deployment of production-grade data pipelines.
• Design resilient workflows with retry logic, failure handling, and resource optimization.
• Proactively address performance and reliability issues and contribute to runbooks and on-call documentation.
• Lead the creation and maintenance of detailed technical documentation for complex pipelines, data models, and system integrations.
• establish and enforce documentation and development standards across projects.
• Mentor junior engineers on clear, consistent coding and documentation habits.
• Act as a key technical partner to product, analytics and data science teams.
• Lead design, discussions, communicate complex data trade-offs with clarity, and proactively surface risks and blockers.
• Support collaborative planning and mentor junior team members in effective communication and partnership.

Benefits

• Health, dental, vision and life insurance plans
• 401(k) Savings plan – with generous company matching contributions (up to 6%)
• Voya Retirement Plan – employer paid cash balance retirement plan (4%)
• Paid time off – including 20 days paid time off, nine paid company holidays and a flexible Diversity Celebration Day.
• Paid volunteer time — 40 hours per calendar year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 251-500 employees