Job Title: Senior Data Analyst
Location: Pittsburgh, PA/ Dallas, TX/ Cleveland, ohio (Hybrid)
Job Type: Full-Time
Experience Level: Senior
PNC Bank is seeking a highly skilled and detail-oriented Senior Data Analyst with strong experience in Python , PySpark , and banking/financial services . This role involves working with large datasets, developing data pipelines, and generating insights to support strategic business decisions.
Design, develop, and maintain scalable data pipelines using PySpark on distributed platforms (e.g., Hadoop, Databricks, or similar).
Perform data extraction, transformation, and analysis using Python , SQL, and Spark.
Collaborate with business stakeholders to gather requirements and deliver actionable insights through dashboards, reports, and data visualizations.
Analyze structured and unstructured data from internal banking systems to support business and regulatory needs.
Partner with engineering and data science teams to operationalize machine learning models and analytics solutions.
Ensure data quality, accuracy, and consistency across analytical solutions.
Document business rules, data flows, and process logic in compliance with data governance standards.
Lead or mentor junior analysts and collaborate with cross-functional teams across product, risk, compliance, and IT.
Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, Statistics, or related field.
5+ years of professional experience in data analytics or data engineering roles.
Strong proficiency in Python (Pandas, NumPy, etc.) and PySpark .
Experience working on distributed data systems such as Hadoop, Hive, or Databricks.
Deep understanding of SQL for querying large datasets.
Prior experience in the banking or financial services industry, with knowledge of core banking functions (e.g., deposits, lending, credit risk, regulatory compliance).
Experience with data visualization tools such as Tableau, Power BI, or Matplotlib .
Strong communication skills and ability to translate complex data into business insights.
Familiarity with cloud platforms (AWS, Azure, or GCP).
Knowledge of data governance, metadata management, and data lineage .
Experience in agile/scrum environments.
Exposure to machine learning or statistical modeling concepts is a plus.
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