Vice President, Platform Engineering

Vice President Of Data Engineering

We are seeking a Vice President of Data Engineering to lead the strategy, design, and delivery of our enterprise data platforms. This role blends technical depth with executive leadership, balancing architecture, team development, and client engagement. The VP will translate complex business needs into scalable solutions, mentor high-performing teams, and provide strategic guidance to clients on data integration and best practices. This is a key leadership role shaping the future of our data ecosystem while ensuring measurable business value.

Responsibilities

Strategy & Leadership

• Define and execute the data engineering strategy to align with enterprise goals and accelerate business insights.
• Lead, mentor, and grow a high-performing engineering team, fostering innovation, accountability, and technical excellence.
• Represent data engineering in executive discussions, external partnerships, and client consultations.

Architecture & Engineering

• Provide architectural oversight across databases, pipelines, APIs, and cloud infrastructure.
• Oversee advanced database administration and schema design, ensuring high performance, scalability, and security.
• Champion modern DevOps and automation practices (CI/CD, GitOps) in data engineering workflows.
• Serve as final escalation point for critical data engineering issues, driving root cause analysis and long-term remediation.

Client & Partner Engagement

• Act as a trusted consultant to clients, advising on data ingestion strategies, delivery mechanisms, and best practices for data structures.
• Translate complex engineering concepts into actionable guidance for both technical and non-technical stakeholders.
• Partner with product, analytics, and business leaders to anticipate data needs and deliver scalable, secure solutions.

Innovation & Optimization

• Lead optimization efforts for high-volume ETL and data processing workflows using Databricks, Python, AWS Glue, and other platforms.
• Drive adoption of Databricks for advanced data engineering, including Data Lake, MLflow integration, and scalable Spark workloads.
• Evaluate and adopt emerging technologies to keep the team at the forefront of data engineering practices.
• Establish and enforce best practices for governance, quality, lineage, and observability, building systems that ensure trusted data.

Qualifications

Desired qualifications and skillsets:

• 10+ years of experience in data engineering, with leadership of large-scale platforms and teams.
• Proven success building and optimizing ETL/ELT solutions with Databricks, AWS Redshift, Glue, S3, and Lambda.
• Expert-level Databricks and Python skills, with a strong background in software engineering best practices.
• Advanced expertise in PostgreSQL (stored procedures, functions, and performance tuning).
• Deep knowledge of APIs, microservices, and event-driven architectures.
• Strong understanding of cloud-native architectures, distributed systems, and modern data modeling.
• Track record of supporting analytics, BI, and data science teams with high-quality, scalable solutions.
• Proven ability to engage with executive-level client stakeholders and influence technical direction.
• Excellent communication and executive presence; able to translate technical concepts into business impact.
• Bachelor's degree in Computer Science, Information Technology, or related field; advanced degree preferred.

The following experience is a plus:

• Experience with BI tools (Tableau, Power BI) and data science ecosystems (Pandas, R, Alteryx).
• Exposure to front-end development and how it connects with backend data models.
• Leadership roles where strategy, technical depth, client engagement, and mentorship intersected.