Job Description
This job was selected by the SpringCube team to help AI, Data and Cloud Engineers discover relevant San Francisco Bay Area employers. Sign up to view the full employer details and apply directly with the hiring company.
Company Overview
A leading online legal services company that combines technology, legal expertise, and attorney-led solutions to help individuals and businesses navigate the legal system. The organization serves millions of customers and uses technology and AI to improve the accessibility, efficiency, accuracy, and safety of legal services.
Responsibilities
- Design, develop, and maintain scalable, reliable, and well-tested data pipelines and ETL/ELT processes using dbt, Snowflake, Airflow, and Fivetran.
- Architect new data models that support business requirements while ensuring high availability, performance, scalability, and extensibility.
- Lead the adoption and integration of modern data engineering practices, including CI/CD, data quality, and data observability.
- Collaborate with cross-functional stakeholders to gather requirements, guide technical decisions, and deliver data solutions aligned with business objectives.
- Mentor and guide data engineers and data scientists while fostering technical excellence and continuous learning.
- Participate in code reviews, architecture discussions, and technical decision-making.
- Monitor industry trends and emerging technologies and advocate for effective data engineering practices.
- Participate in an on-call rotation to respond to high-priority incidents.
- Travel occasionally as required.
Qualifications
- 7+ years of experience in data engineering or a related field, with a demonstrated track record of building and maintaining complex data systems at scale.
- Expert-level proficiency in SQL, including deep experience with data modeling and transformation.
- Hands-on experience using dbt for data transformation and data modeling.
- Experience orchestrating data workflows with Airflow.
- Experience building and maintaining data pipelines with Fivetran, including custom connector development.
- Proficiency in Python for data engineering applications.
- Experience with cloud data warehouses such as Snowflake, Amazon Redshift, or Google BigQuery and modern data stack technologies.
- Strong understanding of ETL/ELT practices, data quality, and data governance.
- Ability to architect and deliver highly available, scalable, and extensible data solutions.
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Experience mentoring and leading engineering teams in an Agile environment.
- Strong understanding of business and product objectives, with the ability to align technical decisions with those goals.
- Remote employees should have internet service with sufficient bandwidth to support required work processes.
AI & Technology Environment
- Experience working in environments where AI capabilities are integrated into business workflows is relevant to the role.
- The organization follows a human-in-the-loop approach in which AI is intended to enhance rather than replace human judgment.
- Candidates may be evaluated on AI fluency, curiosity, and their ability to integrate AI into workflows in measurable and impactful ways.
Disclaimer
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