Staff Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with business stakeholders to identify and prioritize opportunities and initiatives driven by data.

• Design, construct, and maintain scalable data pipelines that support analytics, reporting, product, and operational use cases.

• Develop, test, and refine dbt models adhering to best practices in data modeling.

• Manage and support orchestration platforms such as Airflow and have exposure to Dagster.

• Design and implement dimensional, semantic, and analytical data models.

• Drive decisions regarding data architecture and establish engineering standards and best practices.

• Enhance the reliability, scalability, and performance of the data ecosystem.

• Create and maintain frameworks for data quality, testing strategies, and observability solutions.

• Support governance through documentation, metadata management, lineage, and data ownership practices.

• Conduct complex analyses and provide actionable insights to business stakeholders.

• Oversee team analyses to ensure data accuracy, consistency, and relevance to business needs.

• Advocate for data exploration and the adoption of self-service analytics.

• Lead technical design reviews and offer mentorship through code reviews, architectural guidance, and knowledge sharing.

• Assist in hiring, onboarding, mentoring, and professional development of data engineers.

• Participate in incident response, root cause analysis, and initiatives for continuous improvement.

• Perform other duties as necessary.

⛳️ Requirements

• Bachelor's degree in Computer Science, Data Engineering, Statistics, Information Systems, Business, or a related field.

• 8+ years of experience in data engineering, analytics engineering, or a related area.

• Hands-on expertise with BigQuery, dbt, Airflow, Python, SQL, and modern cloud data platforms.

• Strong grasp of data warehousing concepts, ETL/ELT design patterns, and dimensional modeling.

• Experience in building and optimizing scalable data transformation pipelines within cloud environments.

• Familiarity with Google Cloud Platform services such as BigQuery, Cloud Storage, Pub/Sub, and Cloud Composer.

• Exposure to Azure data platforms and services is advantageous.

• Proficiency in Git-based development workflows, CI/CD pipelines, and software engineering best practices.

• Experience in implementing automated testing, monitoring, and data observability solutions.

• Familiarity with data visualization and exploration tools such as Looker, Mode, Tableau, or similar platforms.

• Exceptional communication and stakeholder management skills, with the ability to convert business requirements into scalable technical solutions.

• Demonstrated ability to lead complex projects and influence technical direction across multiple teams.

🏝️ Benefits

• Competitive compensation package.

• Fun, relaxed work environment.

• Education and conference reimbursements.

• Opportunities for career advancement and mentoring others.

• Bonus eligibility for most non-sales roles.

• Best-in-class benefits with options, expert guidance, and continuous support for employees' physical, financial, and emotional well-being.