3 days ago
Pittsburgh, PA, USAMid Level
Base Salary
$86k - $158k/yr
Responsibilities
- Monitor, maintain, and improve the health, performance, stability, reliability, and scalability of enterprise data platforms.
- Implement platform operations and data engineering standards, including architecture reviews, automation, optimization, right-sizing, and cost reduction.
- Drive migration from legacy Hadoop-based systems to unified, cloud-native data platforms.
- Design and build ETL/ELT pipeline monitoring, intelligent alerts, usage analytics, and dashboards for data platform observability.
- Enhance query performance and data structures and advise internal customers on big data tools and capabilities.
- Partner with business stakeholders to translate analytical needs into scalable technical solutions and actionable business insights.
- Design and implement AI and Generative AI tools, vector database workflows, embedding pipelines, feature stores, and Retrieval-Augmented Generation solutions for automation and platform efficiency.
- Develop, support, and implement data services, infrastructure, migrations, transformations, and data solutions for multiple applications.
Requirements
- Bachelor's degree required; a comparable combination of education, job-specific certifications, and experience may be considered in lieu of a degree.
- Typically 3+ years of relevant or direct industry experience.
- Strong proficiency in Python, Spark, Scala, and SQL, with experience in enterprise database systems such as Oracle and Teradata.
- Experience with modern data engineering, big data ecosystems, scalable data platforms, analytical solutions, and Lakehouse architecture.
- Experience with cloud platforms and data-related services, including Azure or AWS.
- Experience with Apache Iceberg, Apache Airflow, and Trino is highly valued.
- Knowledge of machine learning concepts for automation development.
- Experience with data observability tools such as Monte Carlo and Acceldata, or monitoring stacks such as Datadog, Grafana, and Prometheus, is a plus.
- Ability to contribute to solution design, bridge business and engineering teams, communicate with technical and non-technical audiences, and work cross-functionally.
- Strong problem-solving, critical-thinking, collaboration, data architecture, data governance, data modeling, data pipeline, and data warehousing capabilities.
Benefits
- In-office work arrangement at a PNC location in Pittsburgh, Strongsville, Dallas, Denver, Phoenix, or Birmingham.
- Medical and prescription drug coverage, including a Health Savings Account feature, plus dental and vision options.
- Employee and spouse/child life insurance and short- and long-term disability protection.
- 401(k) with PNC match, pension, and stock purchase plans.
- Dependent care reimbursement, back-up child and elder care, adoption, surrogacy, and doula reimbursement.
- Educational assistance, including select fully paid programs, and a wellness program with financial incentives.
- Paid maternity and/or parental leave, up to 11 paid holidays, 9 occasional absence days, and 15 to 25 vacation days depending on career level and service.
Tech Stack
Apache AirflowApache HadoopApache SparkAWSAzureDatadogDockerGrafanaKubernetesPrometheusPythonScalaSQL
Categories
Data Engineering
About PNC
PNC is a U.S. bank offering retail, business, and corporate banking, including checking, savings, credit cards, mortgages, auto loans, and wealth management. It earns revenue from interest income and fees across consumer, small-business, and institutional clients, and provides digital and branch services nationwide. Headquartered in Pittsburgh, it is a public company listed on the NYSE.