LexisNexis is looking for a Senior Data Engineer to join their Data Engineering team to work across cloud platforms, build scalable data pipelines, support production systems, and design analytics solutions used across engineering and product teams. The role will focus on Databricks development, Redshift administration, engineering analytics, and behavior analytics ingestion, while also providing operational support for critical data pipelines and ensuring high availability, data quality, and platform reliability.
Requirements
- Strong hands-on experience with Databricks, Spark, Delta Lake.
- Advanced proficiency in SQL, including performance tuning and optimization at scale.
- Experience with AWS, especially S3, Lambda, IAM, Redshift, Glue, and Step Functions.
- Strong experience in Redshift administration (performance tuning, distribution/sort keys, cluster optimization).
- Solid Python programming skills for ETL/ELT pipelines, automation, and data engineering tasks.
- Experience working with telemetry, clickstream, or behavioral analytics data.
- Familiarity with Matomo, FullStory, and/or Pendo data processing.
Responsibilities
- Develop, optimize, and maintain large-scale data pipelines using Databricks, Spark, and Delta Lake.
- Implement scalable ETL/ELT patterns for structured, semi-structured data.
- Optimize performance, costs, and reliability of Databricks jobs and clusters.
- Perform Redshift administration tasks including cluster management, and database administration.
- Build and optimize Redshift models, tables, and complex SQL queries to support analytics and reporting.
- Develop and maintain data pipelines powering engineering analytics dashboards and metrics.
- Own ingestion and processing pipelines for behavior analytics and product telemetry, including: Matomo – event and tracking data ingestion, FullStory – behavioral analytics & session replay data, Pendo – product usage, feature analytics, and event telemetry
Other
- Partner with the Data Engineering Lead, Product Management, Analytics, Architecture, and Engineering teams to deliver data solutions that meet evolving business needs.
- Translate technical problems into actionable design documents, code, and operational processes.
- Support downstream consumers with data availability, quality, and documentation.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field required.
- U.S. National Base Pay Range: $93,400 - $155,700.
