Director, Data Engineering

This is a fully remote position, open to applicants in Connecticut, +4 more locations.

📋 Description

• Oversee four data-engineering teams that support the Wealth domain.

• Deliver hands-on technical guidance in areas such as architecture, solution design, implementation, and engineering quality.

• Evaluate technical designs and code while constructively challenging engineering decisions.

• Lead the development and operation of comprehensive data pipelines, emphasizing Databricks and contemporary data-engineering methodologies.

• Set engineering standards for data quality, error management, monitoring, and dependable pipeline development.

• Collaborate with fellow data-engineering directors to create consistent standards, practices, and procedures across various data domains.

• Direct and coordinate initiatives that span engineering teams and business sectors.

• Convert business requirements into effective data solutions while engaging with internal clients, product teams, technology partners, and stakeholders.

• Assist in resolving critical production incidents through problem evaluation, root-cause analysis, and planning for resolutions.

• Cultivate technical talent through coaching, mentoring, feedback, and considerate leadership.

• Promote modern engineering practices, including automation and AI-enhanced development capabilities.

⛳️ Requirements

• Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology, or a related discipline.

• Considerable professional experience in data engineering, featuring progressively responsible technical and leadership roles.

• Proven experience in leading multiple data-engineering teams and/or technical leads.

• In-depth knowledge of SQL, relational database principles, and data architecture.

• Experience in designing, developing, and maintaining modern end-to-end data pipelines.

• Familiarity with Databricks or a similar modern data-processing platform.

• Adequate programming experience to comprehend and review Python or comparable data-engineering code.

• Strong grasp of data quality, error management, observability, and reliable pipeline engineering practices.

• Experience in contributing to technical architecture and solution-design decisions.

• Proven ability to provide technical leadership during significant production incidents.

• Capability to communicate and collaborate effectively across engineering teams and with both technical and business stakeholders.

• Preference for candidates located on the East Coast or who align with Eastern Time working hours.

• Preferred: direct experience with Databricks and Spark.

• Preferred: experience with API and integration concepts within enterprise data architectures.

• Preferred: experience in leading globally distributed or offshore engineering teams.

• Preferred: experience in establishing engineering standards across multiple teams or domains.

• Preferred: experience with Azure, AWS, or Google Cloud Platform.

• Preferred: familiarity with automated data-quality frameworks and established CI/CD practices.

• Preferred: experience in financial services, retirement, wealth management, or investment-related data environments.

• Preferred: knowledge of AI-assisted development, pipeline automation, anomaly detection, or automated data-quality monitoring.

🏝️ Benefits

• Health, dental, vision, and life insurance plans.

• 401(k) Savings plan featuring generous company matching contributions up to 6%.

• Voya Retirement Plan — employer-funded cash balance retirement plan (4%).

• Tuition reimbursement up to $5,250 per year.

• 20 days of paid time off.

• Nine paid company holidays.

• Flexible Diversity Celebration Day.

• 40 hours of paid volunteer time per calendar year.

• Annual cash incentives, sales incentives, and/or long-term incentives based on role and performance objectives.