PNC Bank is seeking a Senior Data Analyst to work with large datasets, develop data pipelines, and generate insights to support strategic business decisions within the banking/financial services industry.
Requirements
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.
Familiarity with cloud platforms (AWS, Azure, or GCP).
Knowledge of data governance, metadata management, and data lineage.
Responsibilities
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.
Other
5+ years of professional experience in data analytics or data engineering roles.
Strong communication skills and ability to translate complex data into business insights.
Lead or mentor junior analysts and collaborate with cross-functional teams across product, risk, compliance, and IT.
Experience in agile/scrum environments.
Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, Statistics, or related field.
