Leads a team of data engineers responsible for building, scaling, and maintaining enterprise data platforms and pipelines. Oversees technical programs, data engineering initiatives, stakeholder alignment, operational excellence, and engineering best practices to deliver reliable, high-quality data solutions supporting analytics, reporting, machine learning, and business decision-making.

What you will do:

Team Leadership & Talent Development

Lead, mentor, and develop a team of data engineers, fostering a culture of accountability, innovation, and continuous improvement.
Establish team objectives, performance expectations, and career development plans.
Recruit, onboard, and retain top engineering talent.
Driving engineering best practices, technical standards, and operational excellence.

Program & Project Management

Own the planning, prioritization, and execution of complex data engineering initiatives.
Develop and maintain program roadmaps aligned with organizational and business objectives.
Manage dependencies, risks, timelines, resources, and stakeholder communications across multiple initiatives.
Ensure projects are delivered on time, within scope, and meet quality standards.

Technical Leadership

Partner with architects and engineering teams to design scalable, secure, and high-performance data solutions.
Guide the implementation of modern data platforms, ETL/ELT pipelines, data lakes, warehouses, and streaming architectures.
Ensure data engineering solutions follow best practices for reliability, observability, governance, and security.
Support architectural reviews and technical decision-making processes.

Stakeholder Management

Partner closely with business leaders, product managers, analytics teams, data scientists, and platform engineering teams.
Translate business requirements into executable technical programs.
Communicate program status, risks, and outcomes to leadership and executive stakeholders.
Drive alignment across technical and business teams.

Operational Excellence

Define and monitor key performance indicators (KPIs) and service-level objectives (SLOs) for data platforms.
Lead incident response, root cause analysis, and continuous improvement efforts.
Implement processes that improve data quality, operational efficiency, and system reliability.
Drive automation and optimization of engineering workflows.

Required Qualifications

5+ years of experience in technology, data engineering, software engineering, or program management.
3+ years of experience leading engineering teams or managing technical programs.
Strong analytical, organizational, and communication skills.
Strong understanding of data engineering concepts, including:
- Data warehousing
- ETL/ELT development
- Data modeling
- Data governance
- Batch and real-time processing
- Data quality management

Compensation Range:

$150,000.00-$160,000.00

Placement in the salary range will be decided upon completion of the interview process. Salary determination will be determined based on factors including but not limited to relevant experience, demonstrated skills related to the requirements of the role, education, certifications, and geographic location.

Equal Opportunity

Bloomberg Industry Group maintains a continuing policy of non-discrimination in employment. It is Bloomberg Industry Group’s policy to provide equal opportunity and access for all persons, and the Company is committed to attracting, retaining, developing, and promoting the most qualified individuals without regard to age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law (“Protected Characteristic”). Bloomberg prohibits treating applicants or employees less favorably in connection with the terms and conditions of employment, in all phases of the employment process, because of one or more Protected Characteristics (“Discrimination”).

Timing