Data Engineering Manager - Customer Data

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineering Manager - Customer Data based in the United States.

As a Data Engineering Manager, you’ll lead the development and maintenance of scalable data solutions that power customer experiences and digital products.
You’ll oversee data engineering teams responsible for customer data, analytics, identity resolution, and data activation capabilities.
The role combines technical leadership, people management, strategic planning, and delivery across a broad portfolio of data initiatives.
You’ll help turn complex customer data into actionable capabilities supporting personalization, omnichannel experiences, and business growth.
You’ll partner with product, technology, and business stakeholders to define roadmaps, prioritize opportunities, and deliver high-quality solutions.
The position also emphasizes talent development, operational excellence, security, and continuous improvement across the data engineering function.
This is a remote leadership opportunity for an experienced data engineering manager who can balance technical depth with strategic thinking and strong team leadership.

Accountabilities

• Lead the development, maintenance, and continuous improvement of data engineering solutions supporting customer data and analytics capabilities.

• Provide technical direction and guidance across customer data, omnichannel identity resolution, data analytics, and personalization-related initiatives.

• Lead and manage data engineering teams, establishing clear objectives, priorities, performance expectations, and delivery plans.

• Build and maintain roadmaps for assigned data products and services, aligning technical investments with broader digital and business strategies.

• Manage end-to-end delivery of digital programs and data initiatives using agile methodologies, design-thinking principles, and established product management processes.

• Translate customer, business, and product needs into scalable data solutions that improve digital experiences and enable personalization.

• Develop data-driven analyses that identify opportunities to improve products, services, customer experiences, and business outcomes.

• Manage project and program portfolios, ensuring initiatives remain aligned with objectives, timelines, resources, quality standards, and expected outcomes.

• Plan and allocate team resources effectively, including coordination with onshore and offshore contractors and external delivery partners.

• Establish and promote quality assurance practices, tools, methods, and standards across the data engineering organization.

• Monitor delivery and team performance, establish objectives for direct reports, provide feedback, and take appropriate action to maintain performance.

• Mentor, coach, and develop data engineers, supporting career growth, technical capability, and long-term team effectiveness.

• Identify training and development needs and provide coaching or knowledge sharing across the wider organization.

• Communicate strategy, priorities, progress, risks, and required actions to team members, senior stakeholders, and business partners.

• Support budgeting and resource planning activities for data engineering programs and initiatives.

• Ensure data engineering activities meet applicable information security requirements and support the identification, analysis, and remediation of cybersecurity risks.

• Encourage adoption of emerging technologies and engineering practices that can improve performance, scalability, efficiency, and customer outcomes.

• Foster an inclusive, collaborative, customer-focused team environment built on trust, accountability, innovation, and continuous improvement.

Requirements

• More than 6 years of relevant professional experience, with substantial experience in data engineering, analytics, technology, or a related discipline.

• Demonstrated experience leading and managing data engineering teams, including hiring, mentoring, performance management, and career development.

• Strong experience providing technical direction and guidance across complex data engineering initiatives.

• Deep experience with customer data, analytics, omnichannel identity resolution, and data science models used to support personalization and customer activation.

• Hands-on or leadership experience with modern data engineering platforms such as Google BigQuery, Snowflake, and Databricks.

• Strong experience modeling complex data and designing scalable data solutions.

• Experience planning and managing resources to deliver projects and programs against defined objectives and timelines.

• Experience managing onshore/offshore teams and leading contractor or external delivery engagements.

• Strong understanding of data engineering practices, architecture, quality, governance, and operational processes.

• Experience managing a portfolio of projects or programs and communicating progress, risks, priorities, and decisions to senior stakeholders.

• Strong strategic mindset, with the ability to translate emerging technology and industry trends into actionable opportunities.

• Strong decision-making skills, including the ability to evaluate competing priorities, trade-offs, risks, and business requirements.

• Excellent communication and collaboration skills, with the ability to build effective partnerships across technical and business teams.

• Strong customer focus and the ability to connect technical solutions to customer needs and measurable business outcomes.

• Demonstrated ability to address difficult issues, make timely decisions, and take ownership of complex challenges.

• Strong coaching and talent-development skills, with a track record of building capable, engaged, and high-performing teams.

• High degree of integrity, accountability, authenticity, and professionalism.

• Strong interest in emerging technologies and the ability to evaluate and adopt tools that can improve engineering performance.

• A Master’s degree or equivalent level of education is preferred.

Benefits

• Targeted annual pay range of $95,200–$158,800 , with individual compensation determined by experience, location, internal pay equity, and other relevant business considerations.

• Competitive total rewards package that may include incentive compensation, equity, and additional benefits.

• Remote work opportunity within the United States.

• Comprehensive benefits program and paid leave offerings in accordance with applicable state requirements.

• Opportunity to lead customer data engineering initiatives with direct impact on personalization and digital customer experiences.

• Leadership opportunity combining technical strategy, team development, program management, and data engineering.

• Exposure to modern data platforms and technologies, including BigQuery, Snowflake, and Databricks.

• Opportunities to mentor and develop data engineering professionals and shape the capabilities of a growing technology organization.

• Collaborative, innovation-focused environment with opportunities to influence digital strategy and transformation.

• Employment offer contingent upon a satisfactory background check, which may include identity verification.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.