Original listing text, shown exactly as published by the company.
About the role
We are looking for an experienced Data Engineering Lead to lead a team of data engineers and own the design, development, and scalability of our data platform. This role combines hands-on technical leadership, data architecture ownership, and people management, with a strong focus on building reliable, scalable, and business-aligned data solutions.
The ideal candidate has 6+ years of experience in data engineering, has worked in fast-paced
startup environments, and is comfortable driving data modeling and architecture decisions
while mentoring and guiding a small team.
Job Code: 2026DATA-065
Job Qualifications
- Technical Leadership & Architecture
- Own and define the data architecture across data warehouses, data marts, and analytical
- layers.
- Lead data modeling initiatives (fact/dimension modeling, analytical schemas) to support reporting, analytics, and advanced use cases.
- Design scalable, reliable, and cost-efficient ETL/ELT pipelines.
- Ensure data platforms are built with performance, scalability, and maintainability in mind.
- Define and enforce best practices for data engineering, including naming conventions,
- documentation, testing, and monitoring.
- Team Leadership & Management
- Lead, mentor, and support a team of data engineers, ensuring technical growth and delivery quality.
- Conduct code reviews, architecture reviews, and technical guidance sessions.
- Foster a culture of ownership, accountability, and continuous improvement.
- Project Ownership & Delivery
- Own data engineering projects end-to-end, from requirements gathering to deployment and post-release support.
- Partner closely with Analytics, Product, Operations, and Business teams to translate requirements into scalable technical solutions.
- Manage priorities, timelines, and dependencies across multiple initiatives.
- Ensure data solutions align with business needs and long-term strategy.
- Data Quality, Reliability & Governance
- Implement monitoring, alerting, and validation to ensure data accuracy and pipeline stability.
- Define data governance standards around data quality, access, and documentation.
- Proactively identify and mitigate risks related to data growth, performance, and system limitations.
Job Qualifications
- 6+ years of experience in data engineering or related roles.
- Proven experience designing and maintaining data architectures and data warehouses.
- Strong expertise in SQL and data modeling techniques (star schema, snowflake,
- dimensional modeling).
- Hands-on experience building ETL/ELT pipelines using modern data tools.
- Experience with cloud-based data platforms (e.g., AWS, GCP, Azure).
- Experience working with large-scale, high-volume data environments.
- Prior experience working in a startup or fast-growing environment.
- Strong problem-solving skills and ability to work in ambiguous, evolving environments.
