Roles & Responsibilities
We are seeking a highly motivated Staff Analytics Engineer to design and scale a robust analytics platform that delivers impactful insights across key domains, such as Subscription, Growth, Identity, Retention, Content, and Product Analytics. As a Staff Analytics Engineer, you will lead efforts to transform raw data into meaningful and actionable insights by building and maintaining a reliable and scalable analytics data infrastructure.
Your work will directly support analysts, data scientists, and business stakeholders by ensuring data pipelines, models, and metrics are effective, accurate, and accessible. This role is critical to driving a data-driven culture and enabling teams to make informed decisions.
Lead the design and development of scalable data pipelines and workflows using Databricks and Apache Spark.
Optimize Spark-based workflows for performance, scalability, and cost efficiency.
Build and maintain reusable data transformations and models using Databricks and Python.
Collaborate with business stakeholders and analysts to define requirements and align data solutions with business needs.
Implement best practices in distributed computing, including performance tuning and cluster management.
Develop and maintain robust documentation and code standards to ensure maintainability and scalability.
Mentor team members in analytics engineering best practices and contribute to building a high-performing team.
Stay ahead of emerging technologies and drive innovation in data engineering practices.
What to Bring:
Bachelors degree in computer science, business analytics or similar discipline.
10+ years of experience in analytics engineering, data engineering, or a related field.
Ability and willingness to learn any new technologies and apply them at work in order to stay ahead of the curve.
Expertise in Databricks and Apache Spark, with hands-on experience optimizing Spark workloads.
Advanced proficiency in Python for data transformation and