This role is for one of the Weekday's clients
Min Experience: 7 years
Location: Remote (India)
JobType: full-time
Department: R&D Engineering Team: Platform Engineering
We are seeking an experienced Engineering Manager—Data Platform to oversee and expand QuillBot’s data infrastructure that supports our product, AI, and growth efforts. Serving over 60M+ users, our data platform plays a vital role in enabling product intelligence, experimentation, usage tracking, and lifecycle marketing.
This position is both technical and strategic—you will lead architectural decision-making, develop high-performance systems, and manage a team of engineers to deliver a dependable, scalable, and cost-effective data platform. Additionally, you will treat the platform as an internal product, ensuring it meets the usability and value needs of cross-functional teams.
Requirements
Key Responsibilities
Technical Leadership & Architecture
- Take ownership of the data platform’s architecture and its ongoing development to support both large-scale real-time and batch data processing.
- Design systems focused on analytics, experimentation, event tracking, and usage metering.
- Maintain high standards for scalability, reliability, performance, and data quality.
- Promote best practices in data engineering, system design, and observability.
Team Leadership & Development
- Build, guide, and manage a high-performing team of data and platform engineers.
- Cultivate a culture that values ownership, innovation, and continuous improvement.
- Offer technical mentorship, support career growth, and oversee performance management.
Cross-functional Collaboration
- Work closely with the Product, AI, Growth, and Marketing teams to understand their data requirements and translate them into scalable solutions.
- Facilitate data-driven decision-making processes across the organization.
Platform as a Product
- Enhance the developer experience and usability of the data platform for internal users.
- Set and monitor platform KPIs, including adoption rates, reliability, and performance metrics.
Performance & Cost Optimization
- Optimize infrastructure to maximize cost efficiency and performance at scale.
- Continuously assess tools, technologies, and processes to improve return on investment.
Generative AI and Automation
- Support AI research efforts by providing data for both training purposes and capability enhancement.
Required Qualifications
- A minimum of 7 years’ experience in software or data engineering, including at least 2 years in engineering management.
- Strong technical expertise and architectural judgment.
- Extensive experience in building and scaling data platforms or distributed systems.
- Hands-on knowledge of backend technologies such as Node.js and the JavaScript ecosystem.
- Practical experience with systems like Spark, streaming technologies, and data pipelines.
- Deep understanding of data pipelines, ETL/ELT processes, and analytics systems.
- Experience working with cloud platforms (AWS, GCP, Azure) and modern data stack tools.
- Proven ability to make architectural trade-offs and lead major technical initiatives.
- Excellent communication skills with a track record of effective cross-functional collaboration.
Preferred Qualifications
- Experience supporting AI/ML projects, experimentation platforms, or growth analytics.
- Familiarity with frontend technologies such as React.js for developing internal tools or dashboards.
- Experience managing data systems at consumer scale (millions of users).
A strong understanding of data governance, privacy, and compliance practices.
Skills
JavaScript
NodeJS
Streaming
Pipelines
Spark
