Intermediate Data Engineer needed at LexisNexis

Responsibilities

• As a senior data engineer on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments. You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets. You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators. You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company. 

You will also:

• Build and scale data infrastructure that powers real-time data processing of billions of records in a streaming architecture
• Build scalable data ingestion and machine learning inference pipelines
• Build general-purpose APIs to deliver data science outputs to multiple business units
• Scale up production systems to handle increased demand from new products, features, and users
• Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs
• Automate and handle the life-cycle of the systems and platforms that process our data

Requirements

• Masters in Software Engineering, Data Engineering, Computer Science or related field
• 2-3 years of relevant work experience
• Strong Scala or Java background
• Knowledge of AWS, GCP, Azure, or other cloud platform
• Understanding of data modeling principles.
• Ability to work with complex data models.
• Experience with relational and NoSQL databases (e.g. Postgres, ElasticSearch/OpenSearch, graph databases such as Neptune or neo4j)
• Experience with technologies that power analytics (Spark, Hadoop, Kafka, Docker, Kubernetes) or other distributed computing systems
• Knowledge of API development and machine learning deployment