About the Role:
The Role: Graph Data Engineer
The Team: We are a central data and reporting function that gathers all organizational data spanning from financial to inventory. This unique position allows our team to innovate and build data products and solutions for internal stakeholders, including applying AI and Machine Learning to our comprehensive datasets. We foster a collaborative environment where continuous learning is encouraged, and team members regularly share knowledge about the latest AI developments and methodologies. The team values experimentation, data-driven decision making, and maintains a culture of intellectual curiosity where interns are mentored by experienced practitioners and given meaningful projects that contribute to real-world applications.
The Impact: The impact of this role lies in building graph-powered data solutions that enhance how AI systems consume and interpret enterprise data, enabling smarter and faster decision-making across the organization. By developing high-quality data products and improving data accessibility, the role directly supports stakeholdersfrom senior leadership to operational teamswith reliable, actionable insights. Additionally, through strong troubleshooting and support practices, it elevates user experience, ensuring scalable, efficient, and continuously improving data and reporting capabilities.
Whatsin it for you:
- You will work with diverse, high-value datasets, solving real-world challenges across data engineering,AgenticAI,graph-based solutions, and reporting.
- Thisrole offers strong learning opportunities through close collaboration with experienced professionals, along with hands-on exposure to building AI-powered data products.
- You will gain end-to-end experiencefrom data extraction and wrangling to engineering and visualizationwhile contributing to impactful, enterprise-wide initiatives.
Responsibilities:
You will be helping build a graph solution that powers AI systems In the day-to-day operations, you will be working with DTS BI Scrum team with the goal to develop cutting edge Data Products for consumption of DTS data by our internal customers which include users from across DTS and the SP Global Enterprise at all levels from senior leadership to individual users. You will also drive Strategic Initiatives that enable us to deliver betterproducts, faster and withworld classsupport. With your acute investigation, troubleshooting and communication skills, you will be championing supportbest practices and improving ourusersexperience. Some of your areas of ownership will include:
Graph database:
- Building knowledge graph and graph rag solutions for AI systems
- Write, test, andoptimizegraph queries for multi-hop traversal, path analysis, and aggregations.
- Tune performance (indexes/constraints, query refactors, batching strategies) and improve reliability (idempotent loads, retry/backoff, backfills).
- Guide leadership and team on Graph Database solutions and implementations.
Data Engineering:
- Data manipulations and transformations either applied in SQL or in Power BI (DAX/Power Query)
- Maintain and update datasets in our Lakehouse/Warehouse
- Maintain data quality in reporting and crafted data.
- Document data manipulations and transformations for use in data dictionary
- Knowledge of Generative AI and its components
Collaboration, Communication and Creative:
- Work closely with the team, product owner, and other stakeholders to understand data requirements and translate them into technical solutions.
- Collaborate with cross-functional teams to design and implement data-driven solutions.
- Strong interpersonal skills with the ability to communicate expert information to non-experts
- Creativity incoming up withsolutions around data and end user experience.
Innovation and Continuous Improvement:
- Stay updated with the latest trends and technologies in data tools and engineering.
- Participate in the development of best practices and guidelines for data management and engineering.
What Were Looking For:
Basic Qualifications:
- 5+ years professional experience as a data engineer or similar role
- B.S. / M.S. in Computer Sciences or related field.
- Knowledge across Graph databases (e.g.Neo4j,GraphDB).
- Understanding of various graph models:
- Property graphmodeling (nodes/relationships/properties) for Neo4j use cases.
- RDF / semanticmodeling (triples,vocabularies/ontologies) forGraphDBuse cases.
- Entity graphpatterns:canonicalentities, identity resolution, deduplication, survivorship rules.
- Hypergraph-stylemodeling needs using patterns likerelationship-as-node(when relationships require attributes, provenance, or n-arysemantics).
- Experience inusing Graphdatabasein AI systems such as Graph RAG.
- Knowledge of and around SQL.
- Programing skills in coding languages specifically for data such as Python.
- Familiarity with cloud data platforms (e.g., AWS, Azure, Google Cloud).
- Knowledge of data lake warehousing concepts and tools (e.g.Snowflake, Databricks, MS Fabric).
- Open to working flexible hours as per business needs.
Preferred Qualifications:
- Some type of certifications in data architecture, engineering, or analytics (e.g., AWS Certified Big Data, Google Cloud Professional Data Engineer, Microsoft Data Engineer).
- Certifications around graph databases or relevant experience
- Proficiencyin graph query languages such as cypher, SPARQL, gremlin or GQL.
- Proficiencyin Python.
- Proficiencyin SQL.
- Utilized AI in general productivity
- Understanding ofEnd-to-End Data to Insightlifecycle.
- Experience with data governance and data security practices.
- Familiarity with machine learning and AI concepts.