Act as an internal consultant for other data engineering and technical teams to enhance and optimize the quality of their code, ensuring adherence to engineering best practices.
Demonstrate initiative to develop approaches to solutions as part of a team; review architecture and identify areas for automation, optimization, right-sized, and cost reduction to support health of the environment.
Design, build and test data integration processes between business-critical applications to solve complex problems within financial services.
Define and implement internal process improvements through the development of detailed analytics that provide actionable insights into key business performance metrics.
Oversight of the development and implementation of data solutions for multiple applications to ensure scalability, availability and maintainability.
Requirements
5+ years of industry-relevant experience
Proven data literacy skills to describe business outcomes, data uses, data sources, and their management concepts and analytical approaches to all organizational levels in both business and technology
Communication and lead experience over a group of data engineers
Demonstrate command of Hadoop, Spark 3m Python, Kafka, and complex orchestration
Consultation on data migration and transformation for accuracy and security of data solutions.
Bachelor's degree
Tech Stack
Hadoop
Kafka
Python
Spark
Benefits
medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service