Data Engineer
$86.25k - $143.75kPNC Bank
Position Overview At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Data Engineer within PNC's Technology organization, you will be based in Pittsburgh, PA or Cleveland, OH. We are seeking a Data Engineer to help support large-scale enterprise big data platforms. This team is responsible for building and evolving modern data solutions that enable analytics across the organization while partnering closely with business stakeholders. Ideal candidates thrive in problem-solving environments, help shape analytical solutions, and contribute to the design of a next-generation, cloud-native data platform. Key Responsibilities:
- Monitor, maintain, and improve the health and performance of the data platform
- Ensure stability, reliability, and scalability of data systems
- Implement best practices for platform operations and data engineering standards. Ensure understanding and adherence across technical and business customers
- Perform frequent reviews of the data platform architecture and identify areas for automation, optimization, right-sizing, and cost reduction to support health of the environment
- Contribute to large-scale transformation initiatives, including:
- Driving user migration to a unified data platform
- Modernizing legacy Hadoop-based systems to cloud-native architectures
- Develop ETL/ELT pipeline monitoring solutions to identify bottlenecks, failures or abnormal data processing metrics
- Establish intelligent alerts to identify high utilization Spark and Trino jobs to ensure service ability for all users
- Capture and report on compute usage across containers in Kubernetes, Docker, etc. to give visibility to job/query optimization needs
- Develop dashboards and visualizations that provide real-time visibility into enterprise data platform health, performance and availability
- Enhance and optimize query performance and data structures to support analytical
- Guide stakeholders in understanding how to leverage data for business insights
- Strong proficiency in relevant programming languages such as Python, Spark, Scala
- Strong background and practical experience in SQL development and enterprise database systems (Oracle, Teradata, etc.)
- Experience with modern, cloud-native and open-source tools is highly valued:
- Apache Iceberg
- Apache Airflow
- Trino
- Strong experience in modern data engineering and big data ecosystems / frameworks
- Hands-on experience working in scalable data platforms and analytical solutions using data lakehouse architecture
- Knowledge and experience with machine learning concepts for automation development
- Familiarity with cloud platforms (e.g Azure , AWS ) and their data related services
- Experience with dedicated data observability tools(Monte Carlo, Acceldata) or broad monitoring stacks (Datadog, Grafana, Prometheus) a plus
- Proven ability to go beyond data movement and contribute to solution design
- Strong communication and presence — able to translate between technical and non-technical audiences
- Proven ability to bridge the gap between business and engineering teams
- Collaborative mindset with experience working across cross-functional teams
- Strong problem-solving and critical thinking skills
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