Lead complex technology initiatives including those that are companywide with broad impact
Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines
Design, code, test, debug, and document for projects and programs
Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors
Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives
Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals
Lead projects, teams, or serve as a peer mentor
Required Qualifications:
5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Additional Required Qualifications:
Strong proficiency in Python for data manipulation, scripting, and building data pipelines.
Extensive experience with PySpark for large-scale data processing and distributed computing.
Deep understanding and hands-on experience with graph databases, specifically Neo4j or TigerGraph.
Proficiency in graph query languages, including Cypher (for Neo4j) or equivalent for TigerGraph.
Proficiency in Graph Modeling, Data pipelines, Query optimization
Good to have expertise/experience with Generative AI (GenAI) products, tools, and frameworks (e.g., LLMs, prompt engineering, fine-tuning, integration with data pipelines).
Experience in GCP cloud, big query
Independently lead and collaborate with business, data scientists and analysts to implement graph-based analytics and AI solutions
Job Expectations:
Lead, mentor, and guide a team of data engineers, fostering a collaborative and high-performing environment.
Architect solutions that leverage graph databases (Neo4j/ Tiger Graph) for complex relationship analysis and knowledge graph construction
Provide technical direction and support to team members, helping them grow their skills and expertise. Conduct code reviews and provide constructive feedback.
Collaborate effectively with data scientists, machine learning engineers, product managers, and business stakeholders to understand data requirements and deliver solutions.
Communicate technical concepts and project status clearly and concisely to both technical and non-technical audiences.
Lead the design, development, and implementation of scalable and efficient data pipelines and architectures, with a particular emphasis on graph data modeling and processing.
Define and enforce best practices for data engineering, including data quality, data governance, and data security.
Evaluate and recommend new technologies and tools to enhance our data platform, with a focus on graph databases and GenAI integration.
