Staff Data Engineer
New
P
PENN Entertainment, Inc.Online Gaming, Sports
Remote, United StatesFull-TimeStaff
Salary160,000 - 205,000 USD per year
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Job Details
- Experience
- 8+ years of experience
- Required Skills
- PythonSQLGCPGitAirflowCI/CDBigQuerydbt
Requirements
- 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 a 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 building and optimizing scalable data transformation pipelines in cloud environments.
- Experience working with Google Cloud Platform services such as BigQuery, Cloud Storage, Pub/Sub, and Cloud Composer.
- Proficiency with Git-based development workflows, CI/CD pipelines, and software engineering best practices.
- Experience implementing automated testing, monitoring, and data observability solutions.
- Experience with data visualization and exploration tools such as Looker, Mode, or Tableau.
- Excellent communication and stakeholder management skills.
- Proven ability to lead complex projects and influence technical direction across multiple teams.
Responsibilities
- Collaborate with business stakeholders to identify and prioritize data-driven opportunities and initiatives.
- Design, build, and maintain scalable data pipelines supporting analytics, reporting, product, and operational use cases.
- Develop, test, and optimize dbt models following data modeling best practices.
- Manage and support orchestration platforms including Airflow and exposure to Dagster.
- Design and implement dimensional, semantic, and analytical data models to support self-service analytics and business intelligence.
- Drive data architecture decisions and establish engineering standards and best practices across the organization.
- Partner with data engineers and platform teams to improve the reliability, scalability, and performance of our data ecosystem.
- Develop and maintain data quality frameworks, testing strategies, and observability solutions to ensure trusted data assets.
- Support governance initiatives through documentation, metadata management, lineage, and data ownership practices.
- Lead technical design reviews and provide mentorship through code reviews, architectural guidance, and knowledge sharing.
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