Data Engineer

FanDuel

$116K — $145K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of experience in data engineering, analytics engineering, or software engineering focused on data
  • Strong SQL skills with familiarity in at least one programming language (Python, Java, or Scala)
  • Hands-on experience with modern data tools such as Databricks, Airflow, dbt, Spark, or Kafka
  • Understanding of data modeling, data warehousing, and ETL/ELT best practices
  • Experience with cloud-based data platforms (AWS, GCP, or Azure)

Responsibilities

  • Design, build, and maintain scalable data pipelines for analytics and business operations
  • Write efficient, well-documented code in tools like Python, SQL, and Spark
  • Ensure reliable and timely data delivery
  • Deliver solutions that support machine learning, data science, and analytics
  • Collaborate with data analysts, scientists, and product managers to deliver actionable data solutions
  • Monitor data pipelines and troubleshoot issues promptly
  • Implement data quality checks and maintain documentation for data sources and architecture

Benefits

  • Flexible work environment with a hybrid model
  • Opportunities for continuous learning and professional development
  • Collaboration with dynamic teams across multiple functions
  • Participation in agile methodologies like sprint planning and code reviews
  • Exposure to innovative technologies and modern data tools
Full Job Description
THE POSITIONOur roster has an opening with your name on it

We are looking for a Data Engineer to join our growing data engineering team and help build the pipelines and infrastructure that power analytics, machine learning, and business decision-making across the company. In this role, you'll contribute to the design, development, and maintenance of reliable data systems while collaborating with stakeholders to support high-impact data use cases.

The ideal candidate is a strong technical contributor who enjoys working with data at scale, solving practical problems, and continuously learning in a fast-paced environment.

If you're excited by this challenge and want to work within a dynamic company, then we'd love to hear from you.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

Build & Maintain Data Pipelines
  • Design, build, and maintain scalable batch and streaming data pipelines to support analytics and business operations.
  • Write clean, efficient, and well-documented code using tools like Python, SQL, and Spark.
  • Ensure data is reliable, accurate, and delivered in a timely manner
  • Deliver solutions supporting ML, DS, Analytics and AI use cases.

Collaborate Across Teams
  • Work with data analysts, data scientists, and product managers to understand requirements and deliver actionable data solutions
  • Translate business questions into engineering tasks and contribute to technical planning.
  • Participate in code reviews, sprint planning, and retrospectives as part of an agile team.

Data Quality & Operations
  • Monitor data pipelines and troubleshoot issues in a timely, systematic manner
  • Implement data quality checks and contribute to observability and testing practices
  • Document data sources, transformations, and architecture decisions to support long-term maintainability


THE STATS
What we're looking for in our next teammate
  • 3+ years of experience in data engineering, analytics engineering, or software engineering with a focus on data.
  • Strong SQL skills and familiarity with at least one programming language (e.g., Python, Java, or Scala).
  • Hands-on experience with modern data tools such as Databricks, Airflow, dbt, Spark, or Kafka.
  • Understanding of data modeling concepts, data warehousing, and ETL/ELT best practices.
  • Experience working with cloud-based data platforms (AWS, GCP, or Azure).
    Preferred Qualifications
    • Experience supporting BI, analytics, or data science teams.
    • Familiarity with version control, CI/CD, and collaborative development workflows.
    • Exposure to data governance, privacy, or compliance practices.
    • Eagerness to learn new technologies and contribute to the growth of the team.

#LI-Hybrid

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