[3 Days Left] Graph DevOps Engineer
1 month ago
As a Knowledge Graph Engineer, you will:
- Develop pipelines and code to support the ingress and egress of this data to and from the knowledge graphs.- Perform basic and advanced graph querying and data modeling on the knowledge graphs that lie at the heart of the organization's Product Creation ecosystem.- Maintain the (ETL) pipelines, code and Knowledge Graph to stay scalable, resilient and performant in line with customer’s requirements.- Work in an international and Agile DevOps environment.
This position offers opportunity to work in a globally distributed team where you will get a unique opportunity of personal development in a multi-cultural environment. You will also get a challenging environment to develop expertise in the technologies useful in the industry.
Primary responsibilities:
- Translate requirements of business functions into “Graph-Thinking”.- Build and maintain graphs and related applications from data and information, using latest graph technologies to leverage high value use cases.- Support and manage graph databases.- Integrate graph data from various sources – internal and external.- Extract data from various sources, including databases, APIs, and flat files.- Load data into target systems, such as data warehouses and data lakes.- Develop code to move data (ETL) from the enterprise platform applications into the enterprise knowledge graphs.- Optimize ETL processes for performance and scalability.- Collaborate with data engineers, data scientists and other stakeholders to model the graph environment to best represent the data coming from the multiple enterprise systems.
Skills / Experience:
Must have:
- Experience in designing and implementing graph data models that capture complex relationships, ensuring efficient querying and traversal.- Strong proficiency and hands-on experience in programming (e.g. Python, Java).- Practical work experience in the development of ontologies and methodologies (i.e. LPG/RDF), ideally in combination with complex data schemes and data modelling- Sound understanding and experience with use of graph databases, graph algorithms and data integration at large scale in complex business networks.- Experience with graph database query languages (e.g. SPARQL), graph algorithms, graph to SQL mapping, graph-based machine learning.- Experience in data integration, ETL processes, ETL tools and frameworks (e.g., Apache Spark, Apache Airflow) and linked data applications using tools like Databricks, Dydra.- Required proficiency in graph databases (e.g., Dydra, Amazon Neptune, Neo4j)
Nice to have:
- Experience with AWS infrastructure (S3, CFTs, EC2), security and data.- Experience with AI pipeline technologies (RDS/Postgres, Snowflake, Airflow) and/or practical experience.- Familiarity with data warehousing and data modeling best practices- Understanding of data visualization tools (e.g., Tableau, Power BI)
Education & Personal skillsets:
- A master’s or bachelor’s degree in the field of computer science, mathematics, electronics engineering or related discipline with at least 2 years of experience in a similar role- Excellent problem-solving and analytical skills- A growth mindset with a curiosity to learn and improve.- Team player with strong interpersonal, written, and verbal communication skills.- Business consulting and technical consulting skills.- An entrepreneurial spirit and the ability to foster a positive and energized culture.- You can demonstrate fluent communication skills in English (spoken and written).- Experience working in Agile (Scrum knowledge appreciated) with a DevOps mindset.
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