Senior Data Engineer
Procter & Gamble20 days ago
Cincinnati, OH, USASenior
Base Salary
$110k - $165k/yr
Responsibilities
- Lead the architecture and implementation of scalable, secure, performant, and cost-efficient data platforms and solutions.
- Design, build, optimize, and operate resilient ETL/ELT pipelines handling petabyte-scale and real-time data workloads.
- Develop complex integrations with enterprise systems, third-party services, streaming sources, APIs, message queues, and data-transfer protocols.
- Define data strategy, architecture, technical roadmaps, engineering standards, governance, and best practices across teams and domains.
- Mentor data engineers and lead code reviews, design discussions, technical workshops, and knowledge-sharing initiatives.
- Own critical data solutions end to end, including deployment, monitoring, performance tuning, observability, anomaly detection, and production incident response.
- Implement data quality, lineage, governance, security, privacy, and responsible AI practices.
- Evaluate and integrate Generative AI models and agentic systems to improve developer productivity and solve complex data problems.
- Use modern development practices including Git strategies, infrastructure as code, and CI/CD pipelines for data platforms.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a closely related quantitative field.
- At least 5 years of progressive data engineering experience delivering large-scale, complex data platforms and pipelines.
- Proven experience leading technical projects, mentoring engineers, and influencing architecture across multiple teams.
- Expert-level Python and SQL proficiency for data manipulation, optimization, performance tuning, and analytics.
- Expert hands-on experience with at least one major cloud platform, with Azure preferred and/or GCP, including cloud data services.
- Extensive experience with distributed data processing technologies such as Spark, PySpark, or Dask, including cluster and resource optimization.
- Expert knowledge of data modeling, data warehousing, data lakes, data mesh concepts, and advanced schema design.
- Experience architecting complex integrations involving APIs, message queues, streaming systems, and enterprise data-transfer protocols.
- Extensive experience with CI/CD, infrastructure as code, and deploying and operating data and machine learning pipelines.
- Practical experience with Generative AI tools and agentic systems, plus knowledge of responsible AI, privacy, security, and ethical considerations.
- Strong communication, presentation, stakeholder-influence, strategic ownership, and continuous-learning abilities.
- Preferred qualifications include Azure data-service expertise or certifications, data governance and MDM experience, real-time streaming, software engineering fundamentals, NoSQL or graph database experience, advanced cloud or Databricks certifications, and MLOps or ML-pipeline collaboration.
Benefits
- Full-time position based at the Cincinnati General Offices.
- Total rewards include salary, bonus where applicable, and benefits.
- Potential opportunities for career growth through mobility, different assignments, locations, and business challenges; candidates should be prepared to consider relocation opportunities.
- P&G provides equal employment opportunities and disability accommodations.
Tech Stack
Apache FlinkApache KafkaApache SparkAzureDatabricksGitGoogle BigQueryGoogle Cloud PlatformMongoDBNeo4jPythonSQLTerraform
Categories
Data Engineering
About Procter & Gamble
Procter & Gamble is a global consumer packaged goods company that makes and sells household, personal care, and hygiene products through retailers and e-commerce. Its portfolio includes brands such as Pampers, Tide, Gillette, Oral-B, and Pantene, serving consumers worldwide. Founded in 1837 and headquartered in Cincinnati, Ohio, P&G is a public company listed on the NYSE under the ticker PG.