Staff Data Engineer: Architect Data Platforms & Analytics

Penn Interactive

United States

Remote

CAD 160,000 - 205,000

Full time

14 days+
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Benefits offered by this job

Competitive compensation package
Fun, relaxed work environment
Education and conference reimburse m
Career progression and mentoring

Job summary

Penn Interactive is seeking a Staff Data Engineer to design and deliver scalable data solutions across analytics, product, and operations. You will lead data architecture decisions, mentor engineers, and partner with stakeholders to drive data-driven outcomes.

Ideal candidates bring 8+ years in data engineering, hands-on BigQuery, dbt, Airflow, and cloud platforms, plus strong communication for cross-team collaboration.

Qualifications

  • Bachelor's degree in Computer Science, Data Engineering, Statistics, Information Systems, Business, or a related field.
  • 8+ years of experience in data engineering, analytics engineering, or related discipline.
  • Hands-on expertise with BigQuery, dbt, Airflow, Python, SQL, and modern cloud data platforms.
  • Strong understanding of data warehousing concepts, ETL/ELT design patterns, and dimensional modeling.
  • Experience with Google Cloud Platform services such as BigQuery, Cloud Storage, Pub/Sub, and Cloud Composer.

Responsibilities

  • Collaborate with stakeholders to identify data-driven opportunities and initiatives.
  • Design, build, and maintain scalable data pipelines for analytics and reporting.
  • Develop, test, and optimize dbt models following best practices.
  • Mentor team members through code reviews, architectural guidance, and knowledge sharing.

Skills

BigQuery
dbt
Airflow
Python
SQL
Cloud platforms

Education

Bachelor's degree in Computer Science or related field

Tools

Looker
Mode
Tableau

Job description

Penn Interactive is seeking a Staff Data Engineer to design and deliver scalable data solutions across analytics, product, and operations. You will lead data architecture decisions, mentor engineers, and partner with stakeholders to drive data-driven outcomes.

Ideal candidates bring 8+ years in data engineering, hands-on BigQuery, dbt, Airflow, and cloud platforms, plus strong communication for cross-team collaboration.

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