VP Data Engineer

BlueSteps Connect; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

BlueSteps Connect is seeking a VP of Data Engineering to lead the data engineering organization, shaping strategy and execution for data pipelines, platforms, and analytics use cases.

You will establish engineering standards, drive scalable data workflows, and ensure data quality and integrity across systems, while collaborating with cross-functional stakeholders to align technical delivery with business goals.

Qualifications

• Leadership experience in data engineering or related roles.
• Ability to guide teams and deliver complex data initiatives.
• Deep technical knowledge in building and operating data pipelines and platforms.

Responsibilities

• Lead design, development, and maintenance of data pipelines and data platforms.
• Establish engineering standards and drive scalable, reliable data workflows.
• Ensure data quality and integrity across systems.
• Collaborate with cross-functional stakeholders to align delivery with business needs.

Skills

Leadership

Data Engineering

Data Pipelines

Cross-functional Collaboration

Communication

Job description

the client is seeking a VP of Data Engineering to lead and manage data engineering efforts. This role will oversee the design, development, and maintenance of data pipelines and data platforms that enable reliable data access and analytics use cases.

The VP of Data Engineering will be responsible for establishing engineering standards, driving scalable and efficient data workflows, and ensuring data quality and integrity across systems. The role typically involves collaborating with cross‑functional stakeholders to align technical delivery with organizational needs and to improve performance, reliability, and maintainability of data infrastructure.

The ideal candidate will have strong leadership experience in data engineering or related roles, with a proven ability to guide teams and deliver complex data initiatives. The role is expected to require deep technical knowledge in building and operating data pipelines, as well as effective communication to support planning, execution, and continuous improvement across the data engineering organization.