Engineering Manager, Data Platform Hybrid - San Francisco

$285,000 - $325,000/Yr

Grammarly - San Francisco, CA

Full-time - Mid Level

Hybrid - San Francisco, CA

251-500 employees

Publishing Industries

About the position

The Engineering Manager for the Data Platform at Grammarly will lead a specialized team focused on building and maintaining a robust data infrastructure to support the company's ambitious goals. This role involves overseeing the design, implementation, and governance of data systems, ensuring high performance and reliability while fostering a collaborative environment for professional growth. The manager will play a crucial role in aligning data strategies with business objectives and mentoring a high-performing team of data engineers and specialists.

Responsibilities

• Build a highly specialized data platform team to support the growing needs and complexity of our product, business, and ML organizations.
• Oversee the design, implementation, and maintenance of a robust data infrastructure, ensuring high availability and reliability across ingestion, processing, and storage layers.
• Lead the development of frameworks and tooling that enable self-serve analytics, policy management, and seamless data governance across the organization.
• Ensure data is collected, transformed, and stored efficiently to support real-time, batch processing, and machine learning needs.
• Act as a liaison between the Data Platform team and the broader organization, ensuring seamless communication, collaboration, and alignment with global data strategies.
• Drive cross-functional meetings and initiatives to represent the Data Platform team's interests and contribute to the organization's overall data strategy, ensuring ML and analytics use cases are adequately supported.
• Drive the evaluation, selection, and implementation of new technologies and tools that enhance the team's capabilities and improve the organization's overall data infrastructure and governance processes.
• Implement and enforce data governance policies and practices to ensure data quality, privacy, security, and compliance with organizational standards.
• Collaborate with stakeholders to define and refine data governance policies that align with business objectives and facilitate discoverability and accessibility of high-quality data.
• Monitor and assess the data platform's performance to identify areas for optimization, cost management, and continuous improvement.
• Foster a collaborative and high-performance culture within the team, emphasizing ownership and innovation.
• Cultivate an ownership mindset and culture across product and platform teams by providing necessary metrics to drive informed decisions and continuous improvement.
• Set high performance and quality standards, coaching team members to meet them, and mentoring and growing junior and senior IC talent.

Requirements

• 7+ years of experience in data engineering, infrastructure & governance, with at least 2-3 years in a leadership or management role.
• Proven experience in building and managing large-scale data platforms, including data ingestion pipelines and infrastructure.
• Experience with cloud platforms and data ecosystems such as AWS, GCP, Azure, and Databricks.
• Familiarity with modern data engineering and orchestration tools and frameworks (e.g., Apache Kafka, Airflow, DBT, Spark).
• Strong understanding of data governance frameworks, policy management, and self-serve analytics platforms.
• Excellent leadership and people management skills, with a track record of mentoring and developing high-performing teams.
• Experience working with geographically distributed teams and aligning with global data and governance strategies.
• Strong problem-solving skills, with the ability to navigate and resolve complex technical challenges.
• Excellent communication and collaboration skills, with the ability to work effectively with stakeholders across different locations and time zones.
• Proven ability to operate in a fast-paced, dynamic environment where things change quickly.

Nice-to-haves

• Experience with machine learning use cases and analytics engineering.
• Familiarity with data privacy regulations and compliance standards.

Benefits

• Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
• Disability and life insurance options
• 401(k) and RRSP matching
• Paid parental leave
• 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and unlimited sick days
• Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
• Annual professional development budget and opportunities