PNC is seeking a Data Analyst to build and maintain data infrastructure for their marketing team, enabling data-driven decisions, customer engagement, and business growth.
Requirements
- Strong proficiency in Python, SQL and Spark is essential.
- Hands-on experience with modern cloud data warehouses like Snowflake, Big Query, or Amazon Redshift.
- Experience building and managing ETL/ELT pipelines using tools like Apache Airflow, or similar technologies.
- Experience with at least one major cloud provider (AWS, or Azure).
- Solid understanding of data modeling principles (e.g., star schema, snowflake schema).
- Experience with real-time data streaming technologies (e.g., Kafka, Kinesis).
- Familiarity with marketing platforms and their APIs (e.g., Adobe Analytics, Salesforce Marketing Cloud, Google Ads).
Responsibilities
- Build, test, and maintain robust data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.
- Collaborate with marketing and analytics teams to design and implement efficient data models that support reporting, ad-hoc analysis, and machine learning initiatives.
- Help design, manage and optimize our data infrastructure, including data warehouses, data lakes, and data orchestration tools (e.g., Airflow).
- Implement processes and tools to ensure data accuracy, consistency, and reliability. Monitor data pipelines for issues and proactively resolve them.
- Establish and maintain data governance best practices within the marketing data ecosystem.
- Optimize queries and data structures to improve the performance and efficiency of data access for analysts and data scientists.
- Stay current with the latest data engineering technologies and methodologies and propose new solutions to improve our data platform.
Other
- This position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis.
- Some responsibilities may be performed remotely, at manager’s discretion.
- Excellent problem-solving skills and attention to detail.
- Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- A proactive and collaborative attitude, with a passion for building data solutions that deliver real business value.
