Data Engineer

FanDuel

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Atlanta, GA
Salary: $116,000–$152,250 / yr
Posted: 6 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $164k

This role $134k

$106k $213k

below market most similar roles pay here above market

This role pays less than 64% of similar roles. Most pay $126,800–$202,200 — the blue band above. At the midpoint, this role pays about $134k versus about $164k for comparable roles.

Based on 240 similar postings.

Employer

About FanDuel

FanDuel is a leading online sports betting and daily fantasy sports platform operating across the United States, offering sportsbook wagering, casino games, and horse racing to millions of customers.

FanDuel currently has 47 open roles on FindRole.

Listed pay typically runs $116,000–$173,000 across 47 roles with salary data.

Most-posted roles

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At a glance

TL;DR · Data Engineer

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The Data Engineer - FanDuel Careers joins the Data Support team to ensure the reliability and performance of critical data pipelines and infrastructure. This role involves providing on-call technical assistance to analysts and engineering teams, resolving data quality issues, and investigating reporting anomalies or failed jobs. You will design and implement batch and real-time data pipelines to the data warehouse or data lake while creating technical documentation and automation solutions. Key technologies include SQL, Python, AWS, Databricks, Spark, Kafka, Kinesis, and Airflow. You will also utilize Datadog, DataFold, Monte Carlo, Prometheus, and Grafana. The position focuses on maintaining data health, optimizing queries, and managing incident response to ensure the delivery of accurate, timely, and consumable data for informed business decision-making.

What does a Data Engineer earn?

Median $159000 from 203 postings across 58 companies.

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Skills

SQL Python AWS Databricks Spark Kafka Kinesis Airflow Datadog Prometheus Grafana Dbt CI/CD BuildKite GitHub Actions Tableau Looker ETL ELT Machine Learning AI

What you'll do

Provide on-call technical assistance for query optimization, reporting anomalies, and complex data pipeline issues.
Investigate and resolve data quality issues triggered by system alerts or stakeholder notifications.
Design and implement batch and real-time data pipelines using data transformation technologies.
Identify operational inefficiencies and implement automation solutions to reduce manual intervention.
Create and maintain technical support documentation, including FAQs, troubleshooting steps, and runbooks.
Drive operational best practices for incident management, monitoring, and routine consumer support.
Administer account access to tools across the technology stack according to governance policies.
Participate in an on-call pager duty rotation to ensure 24/7 coverage for critical issues.

What we're looking for

Minimum of 3+ years of experience in data engineering with a focus on operational support.
Advanced SQL skills with proven experience in query optimization.
Proficiency in Python programming for automation and data processing.
Experience with cloud data platforms including AWS, Databricks, and Spark.
Understanding of data warehousing, ETL/ELT processing, dimensional data modeling, and batch/real-time data ingestion.
Working knowledge of orchestration and monitoring tools such as Airflow, Datadog, and Grafana.
Experience with data streaming patterns and tools like Dbt (preferred).
Familiarity with CI/CD practices for data pipelines and data visualization tools like Tableau or Looker (preferred).

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