Engineering Manager, Enterprise Data Platform

Engineering Manager, Enterprise Data Platform

As a Data Engineering Manager within the Enterprise Data Platform team, you

will lead a team of skilled data engineers responsible for building and optimizing data

pipelines, managing large-scale data models, and ensuring the quality, availability, and

performance of enterprise data assets. This leadership role combines technical depth,

strategic thinking, and people management to enable data-driven decision-

making and analytics capabilities.

Youll collaborate closely with cross-functional partners across Technology & Engineering,

Product, Sales, Marketing, Research, Finance, and Administration to deliver robust,

scalable data solutions. The ideal candidate is a hands-on leader with a strong background

in modern data platforms, cloud architecture, and team developmentsomeone

passionate about empowering teams and improving data capabilities across the

organization.

This is both a strategic and hands-on leadership role: you will guide architectural decisions,

mentor engineers, collaborate with cross-functional leaders, and contribute to building

next-generation data and AI capabilities . You will exhibit a growth mindset, be

willing to solicit feedback, engage others with empathy, and help create a culture of

belonging, teamwork, and purpose. If you love leading a team of passionate data

engineers, building data-centric solutions, strive for excellence every day, are adaptable

and focused, and believe work should be fun, come join us!

Primary Job Responsibilities

• Lead, mentor, retain top talent and develop a team of data engineers, fostering a

culture of excellence, accountability, and continuous improvement

• Define and drive the data engineering roadmap aligned with enterprise data strategy

and business objectives

• Collaborate with senior technology and business leaders to define data platform

priorities, architecture, and long-term vision

• Promote a culture of innovation, operational rigor, and customer empathy within the

data organization

• Oversee the design, development, and maintenance of high-quality data pipelines

and ELT/ETL workflows across enterprise systems and platform

• Ensure scalable, secure, and reliable data architectures using modern cloud

technologies (e.g., Snowflake, Airflow, Kafka, Docker)

• Lead AI learning initiatives and integrate AI/ML-driven solutions into data products

to enhance automation, predictive insights, and decision intelligence

• Champion data quality, governance, lineage, and compliance standards across the

enterprise data ecosystem

• Partner with engineering and infrastructure teams to optimize data storage,

compute performance, and cost efficiency

• Support career development through mentoring, skill-building, and performance

feedback

Skills and Qualifications

• Bachelors or Master’s degree in Computer Science, Engineering, or a related field

• 8+ years of experience in data engineering or related roles, including at least 2–3

years of leadership experience managing technical teams

• Proven experience designing and maintaining large-scale data architectures,

pipelines, and data models in cloud environments (e.g., Snowflake, AWS, Azure, or

GCP)

• Advanced proficiency in SQL and Python for data manipulation, transformation, and

automation

• Deep understanding of ETL/ELT frameworks, data orchestration tools (e.g., Airflow),

and distributed messaging systems (e.g., Kafka)

• Strong knowledge of data governance, quality, and compliance frameworks

• Experience working with enterprise data sources (CRM, ERP, Marketing Automation,

Financial Systems, etc.) is preferred

• Hands-on experience with AI/ML platforms, model deployment, or data-driven

automation is a strong plus

• Excellent communication and stakeholder management skills with the ability to

translate complex data concepts into business value

• Demonstrated ability to build high-performing teams and lead through change