Analytics Engineer: Data Pipelines & Dashboards

Omaze; Jersey City (NJ); On-site; USD 116,000 - 152,250; Full time

Job summary

FanDuel is seeking an Analytics Engineer for the Sports Modeling & Innovation team to design, build, and enhance data models, datasets, and visualizations used by data scientists and business stakeholders.

You will bridge data between Data Engineering and analytics, improving data-driven decisions while nurturing curiosity and a passion for learning. The role involves multiple teams and evolving business needs.

Qualifications

• 3+ years in analytics or data engineering roles.
• 2+ years maintaining databases with a focus on data ingestion pipelines.
• Deep understanding of relational databases.
• Proficient in SQL, Databricks, R/Python, Tableau, AWS S3, and command line.
• Experience building data pipelines using Python/R and Databricks.
• Bachelor's Degree in Math, Stats, Econ, or related field.
• Strong organizational and time management skills.
• Ability to work in a fast-paced environment.
• Strong problem-solving skills.
• Experience working in groups on collaborative projects.

Responsibilities

• Develop pipelines to ensure fast data ingestion into databases (SQL, Delta Lakes).
• Maintain validation pipelines that flag bad or missing data.
• Manage and optimize data transformation jobs for the Sports Modeling and Innovation team.
• Automate data cleaning projects on large data sets.
• Create and own backlog of Tableau dashboards / Rshiny app additions.
• Curiosity about AI and emerging technologies is a plus.

Skills

Analytical thinking

Problem-solving

Time management

Team collaboration

Data-driven decision making

Education

Bachelor's degree in Math/Stats/Econ or related field

Tools

SQL

Databricks

R

Python

Tableau

AWS S3

Command line

Job description

FanDuel is seeking an Analytics Engineer for the Sports Modeling & Innovation team to design, build, and enhance data models, datasets, and visualizations used by data scientists and business stakeholders.

You will bridge data between Data Engineering and analytics, improving data-driven decisions while nurturing curiosity and a passion for learning. The role involves multiple teams and evolving business needs.