Staff Analytics Engineer

LastPass is looking for a Staff Analytics Engineer.

As a Staff Analytics Engineer, you will design, build, and maintain the data infrastructure and pipelines that empower our data team to enhance operational performance. You’ll collaborate closely with data scientists, security analysts, and product teams to transform business needs into scalable data solutions, ensuring our ability to effectively serve our customers.

If you are passionate about complex problem solving and motivated by scale, then this is the role for you!

Who will you work with?

As a Staff Analytics Engineer, you will collaborate with leaders across Marketing, Sales, Finance, and Product organizations to deliver impactful data solutions. You’ll also partner with Engineering to uphold a high standard of data governance.

What are some of the exciting challenges you will be working on?

• Design and build scalable, reliable, and efficient ETL pipelines to process and transform data from various sources.
• Collaborate with data scientists and analysts to ensure data is easily accessible, clean, and enriched for downstream analysis.
• Develop and maintain the company's data warehouse and analytics infrastructure using best practices to support data-driven decision-making.
• Partner with engineering teams to create and maintain data models that power key business metrics.
• Contribute to the company’s data strategy, focusing on data quality, governance, and compliance.
• Lead efforts to implement monitoring and alerting on data pipelines to ensure the reliability and accuracy of key data assets.
• Optimize the performance of data systems, reducing query times and ensuring data availability for critical business operations.
• Mentor and provide technical guidance to junior analytics engineers and data team members.

What does it take to work at LastPass?

• We value collaboration, innovation, and integrity. Our ideal candidate embraces diversity, is eager to learn, and thrives in a dynamic environment.

It's great, but not required:

• Experience in data engineering, analytics engineering, or a similar role, preferably in the cybersecurity or tech industry.
• Proficiency with SQL and experience working with relational databases and data warehouses (e.g., Snowflake, Databricks).
• Familiarity with Python for data processing.
• Experience with Kimball data modeling, data warehousing, and designing efficient, scalable data architectures.
• Excellent communication skills and the ability to collaborate with cross-functional teams.
• Strong problem-solving skills, attention to detail, and a proactive mindset.
• Strong proficiency with AWS Cloud Services (S3, Redshift, EC2, Lambda, RDS, etc.).
• Experience with Terraform or CloudFormation for infrastructure as code (IaC) in AWS environments.
• Familiarity with CI/CD pipelines for automated data workflow deployment.
• Experience working in an Agile environment and managing sprint-based project cycles.

Our compensation reflects the cost of labor across several US geographic markets. The typical base pay range for this role across the U.S. is USD $144,500 in the lowest geographic market and up to $171,000 per year in our highest geographic market. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.