Job Summary
We are seeking a highly skilled Software Engineering Director with proven expertise in designing, building, and scaling data solutions. This role combines hands-on technical leadership with strategic thinking and requires the ability to lead, mentor, and inspire software and data engineering teams. The individual will drive the technical strategy, design, and implementation of data platforms and distributed systems that enable advanced analytics, AI/ML, and business intelligence across the organization.

Key Responsibilities
• Drive technical strategy, architecture, design, and implementation of scalable software and data solutions.
• Lead, mentor, and influence software and data engineering teams while establishing engineering practices and technical standards.
• Design and deliver distributed systems using Java, Spring, Spring Boot, Microservices, RESTful APIs, and GraphQL APIs.
• Develop and maintain applications using Spark frameworks with Python, Scala, and the Spark ecosystem.
• Design and implement scalable data pipelines and ETL/ELT processes supporting enterprise reporting and analytics.
• Process and analyze large-scale datasets and develop solutions for data-intensive applications.
• Design and implement near real-time data processing, stream-based integrations, and data serialization solutions.
• Apply data fabric concepts including data virtualization, metadata-driven orchestration, and semantic layers.
• Design and implement data models and apply common information models.
• Drive modern data analytics and AI/ML integration using technologies such as SageMaker, Tableau, and Snowflake Spectrum.
• Design and implement solutions involving RAG systems, data ingestion pipelines, and embedding-driven retrieval systems.
• Establish and maintain CI/CD pipelines and modern DevOps/DataOps practices using Git, Terraform, Jenkins, pipelines, and containerization.
• Design and implement API security and integration capabilities using OAuth, API Management, Service Mesh, ActiveMQ, and scheduling technologies.
• Work with RDBMS, GraphDB, MongoDB, advanced SQL, object storage such as S3 and Blob, Redis, and DataMarts.
• Establish and promote Data Governance practices covering Master Data Management, Data Quality Management, metadata management, lineage, and cataloging.
• Support applied Generative AI and LLM-based solutions within enterprise software and data environments.
• Collaborate with stakeholders to translate business requirements into technical solutions and actionable development roadmaps.
• Create and articulate application technical designs, decompose designs into development tasks, size efforts, and establish delivery roadmaps.
• Ensure technical decisions align with business objectives and responsible AI practices.
• Build consensus across cross-functional teams while driving technical excellence and pragmatic delivery.
• Provide technical guidance and mentorship while elevating team capabilities and promoting knowledge sharing.

Required Qualifications
• 10+ years of hands-on software development experience, including Java, .NET, Python, AWS, Microservices, Kubernetes, and recent Angular versions.
• 15+ years of non-internship professional experience in software engineering, with at least 5+ years in data engineering.
• 10+ years of experience designing, developing, delivering, and supporting distributed systems using Java, Spring, Spring Boot, Microservices, RESTful APIs, and GraphQL APIs.
• 4+ years of experience developing and maintaining applications using Spark frameworks, with strong programming skills in Python, Scala, and the Spark ecosystem.
• 7+ years of leadership experience managing, mentoring, and influencing software and data engineering teams.
• Strong expertise in processing and analyzing large-scale datasets.
• Strong knowledge of object-oriented design, data structures, and algorithms.
• Experience with AWS, GCP, or Azure and their associated data services.
• Experience with cloud-native architectures, Kubernetes, and containerization.
• Strong knowledge of data fabric concepts, including data virtualization, metadata-driven orchestration, and semantic layers.
• Experience with near real-time data processing, stream-based integrations, and data serialization formats.
• Experience with data modeling and common information models.
• 5+ years of experience working with Agile practices in enterprise software environments.
• At least 1 year of applied experience with Generative AI or LLM-based solutions.
• Experience with modern data analytics and AI/ML integration, including technologies such as SageMaker, Tableau, and Snowflake Spectrum.
• Hands-on experience with CI/CD, DevOps, and DataOps practices using Git, Terraform, Jenkins, pipelines, and containerization.
• Experience designing, implementing, and maintaining scalable data pipelines and ETL/ELT processes.
• Experience with Data Governance disciplines including Master Data Management, Data Quality Management, metadata management, lineage, and cataloging.
• Experience with OAuth implementation, API Management, Service Mesh, ActiveMQ implementations, and batch job schedulers.
• Experience with RDBMS, GraphDB, MongoDB, advanced SQL, S3, Blob storage, Redis, and DataMarts.
• Experience solving complex problems in algorithm-heavy and data-intensive applications.
• Knowledge of RAG systems, data ingestion pipelines, and embedding-driven retrieval systems.
• Excellent communication skills with the ability to translate technical concepts for technical and non-technical audiences.
• Proven experience influencing business outcomes through technical solutions.
• Strong stakeholder management, problem-solving, design thinking, and decision-making skills.
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.