Senior Data Engineer - Analytics

San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Generative AI, Legal TechIndustries

Requirements

Candidates should have 4+ years of experience as a Data Engineer, Analytics Engineer, or Business Intelligence Engineer, preferably in product-focused, fast-paced environments. Strong experience with designing dimensional models and defining clear source-of-truth metrics is required. Proficiency in SQL for data transformation and comfort in at least one functional/OOP language such as Python or Scala for data wrangling or orchestration logic are essential. Expertise in creating reporting and data visualization solutions using dashboarding tools like Looker, Tableau, or Metabase is necessary. The ideal candidate is a self-starter with excellent communication and interpersonal skills, comfortable working in fast-paced, evolving environments, and has strong attention to detail and structured thinking.

Responsibilities

The Senior Data Engineer - Analytics will partner with product, analytics, and operations teams to understand data needs and translate them into scalable models and pipelines. They will build and maintain robust ELT pipelines using tools like dbt, Airflow/Dagster, and Snowflake, and own the design and evolution of data models that support reporting, experimentation, and product feature instrumentation. Responsibilities also include improving data quality and reliability through testing, monitoring, and alerting practices, driving data architecture forward with a focus on usability, performance, governance, and scalability, and mentoring other engineers and analysts on data best practices.

Skills

Data Engineering

Analytics

ELT pipelines

dbt

Airflow

Dagster

Snowflake

Data Modeling

Data Quality

Data Governance

Generative AI

ETL

EvenUp

Legal services for personal injury cases

About EvenUp

EvenUp Law provides legal services focused on personal injury, trucking accidents, and medical malpractice. The firm operates in multiple states, including Texas, Pennsylvania, California, Indiana, and Georgia. Its business model is based on a contingency fee structure, meaning they only receive payment if they win a case, taking a percentage of the settlement or judgment. What sets EvenUp Law apart from its competitors is its detailed case preparation and the ability to analyze cases like an adjuster or defense attorney, which leads to higher settlement amounts and quicker resolutions for clients. The firm also maintains a database of similar injuries and their values, which helps in providing accurate damage estimates. The goal of EvenUp Law is to save clients time and stress while ensuring they receive fair compensation for their injuries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$214MTotal Funding

SERIES_DCompany Stage

LegalIndustries

201-500Employees

Risks

Increased competition from other legal tech startups could erode EvenUp's market share.

Reliance on a contingency fee model poses financial risks with unsuccessful cases.

Potential regulatory changes in AI use could impact EvenUp's operations.

Differentiation

EvenUp uses AI to automate legal document creation, reducing time and costs.

The company targets the $20 million insurance claim market with AI-driven solutions.

EvenUp's meticulous case preparation results in high settlement amounts and quick resolutions.

Upsides

Recent $135 million Series D funding shows strong investor confidence in EvenUp.

Launch of AI assistant Litty highlights growth in generative AI for legal automation.

Strategic board appointments could open new avenues for growth and partnerships.

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