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Lead Software Engineer (Big Data; SPARK)

About the position

We are seeking a highly motivated Lead Software Engineer to join our Enterprise Finance Technology organization. This role will provide technical leadership in the design, development, implementation, and modernization of critical accounting, finance, and regulatory reporting platforms. The successful candidate will lead engineering teams in delivering scalable, secure, and resilient solutions that support financial transaction processing, accounting engines, regulatory reporting, data integration, and enterprise data platforms. This role requires deep expertise in distributed systems, cloud technologies, data engineering, event-driven architectures, and financial systems integration, along with hands-on experience using Python and Spark.

Responsibilities

Lead the architecture, design, and development of enterprise-wide finance technology solutions.
Drive modernization initiatives focused on cloud-native platforms, containerization, automation, and scalable data processing.
Design and implement high-performance data pipelines using Python, Apache Spark, Kafka, and modern data engineering frameworks.
Lead integration efforts between Oracle E-Business Suite (EBS), accounting platforms, regulatory reporting systems, and enterprise data warehouses.
Develop and support financial transaction processing services, accounting engines, reconciliation platforms, and reporting applications.
Partner with Accounting, Finance, Risk, Audit, Regulatory Reporting, and Technology stakeholders to define technical solutions aligned with business objectives.
Establish engineering standards, architecture patterns, coding best practices, and operational excellence processes.
Design event-driven architectures leveraging Kafka and streaming technologies to support near real-time financial processing and reporting.
Drive adoption of DevOps, CI/CD pipelines, infrastructure-as-code, automated testing, and deployment automation.
Lead root cause analysis for complex production issues and implement long-term remediation strategies.
Ensure solutions meet enterprise security, resiliency, compliance, data governance, and regulatory requirements.
Provide technical leadership, mentorship, and coaching to software engineers and technical leads.
Collaborate with enterprise architecture, cybersecurity, cloud engineering, and infrastructure teams to implement platform modernization strategies.
Evaluate emerging technologies and recommend innovative solutions to improve operational efficiency, scalability, and reliability.

Requirements

5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of Python and object-oriented software development experience.
5+ years of hands-on experience with Apache Spark for large-scale data processing and analytics.
5+ years of technical leadership experience leading complex initiatives and engineering teams.

Nice-to-haves

Experience designing and implementing Kafka-based messaging and event-streaming solutions.
Strong knowledge of APIs, microservices architecture, and distributed systems design.
Experience with relational databases including Oracle, SQL Server, PostgreSQL, or equivalent platforms.
Hands-on experience with cloud platforms including Azure, AWS, or Google Cloud.
Experience implementing CI/CD pipelines using modern DevOps tools and practices.
Strong understanding of software security, data privacy, resiliency, monitoring, and observability
Experience supporting Oracle E-Business Suite financial modules and integrations.
Knowledge of General Ledger, Accounts Payable, Accounts Receivable, Fixed Assets, and Subledger Accounting processes.
Experience with Accounting Hub, enterprise accounting engines, or financial transaction processing platforms.
Experience supporting regulatory reporting solutions and financial reporting controls.
Familiarity with enterprise finance systems including Oracle ERP, SAP, or comparable platforms.
Experience with OpenShift, Kubernetes, Docker, or container-based deployments.
Experience implementing data governance, data lineage, and auditability requirements.
Knowledge of enterprise integration patterns and middleware technologies.
Experience working in regulated financial services environments.