Data Engineer: Build Scalable Pipelines & Insights (Hybrid)

FanDuel; Atlanta (GA); Hybrid; USD 116,000 - 145,000; Full time

Benefits offered by this job

Health plans and benefits

PTO and sick leave

Annual bonus and long-term incentive

401k with up to 5% match

Commuter benefits

Pet insurance

FanDuel Total Rewards

Job summary

FanDuel is seeking a Data Engineer in Atlanta to join our data engineering team. You will own the design, development, and maintenance of reliable data systems powering analytics and business decisions.

You will work with stakeholders to translate questions into engineering tasks and deliver scalable data products. You will collaborate with data analysts, data scientists, and product managers in a fast-paced, agile environment, applying best practices for data quality, observability, and

Qualifications

• 3+ years of experience in data engineering, analytics engineering, or software engineering with a focus on data.
• Strong SQL skills and familiarity with Python, Java, or Scala.
• Hands-on experience with Databricks, Airflow, dbt, Spark, or Kafka.
• Understanding of data modeling, warehousing, and ETL/ELT best practices.
• Experience with cloud data platforms (AWS, GCP, or Azure).

Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines to support analytics and business operations.
• Write clean, efficient, and well-documented code using Python, SQL, and Spark.
• Ensure data is reliable, accurate, and delivered in a timely manner.
• Lead projects to build or improve well-scoped data products.
• Collaborate with data analysts, data scientists, and product managers to deliver actionable data solutions.

Skills

SQL

Python/Java/Scala

Data at scale

Agile, collaboration

Data modeling

Cloud platforms

Tools

Databricks

Airflow

dbt

Spark

Kafka

Job description

FanDuel is seeking a Data Engineer in Atlanta to join our data engineering team. You will own the design, development, and maintenance of reliable data systems powering analytics and business decisions.

You will work with stakeholders to translate questions into engineering tasks and deliver scalable data products. You will collaborate with data analysts, data scientists, and product managers in a fast-paced, agile environment, applying best practices for data quality, observability, and