Senior Data Engineer

Support an analytical data infrastructure providing application, tool and ad-hoc access to large datasets consisting of complex data types including genomic, phenotypic, environmental, image and geospatial data.

Lead, coach and develop more junior engineers and IT professionals.

Engage with business stakeholders to understand strategic roadmaps and build a technical strategy to support them.

Interface with DevOps teams to extract, load and transform data from a wide variety of data sources using big data technologies in AWS cloud including Glue, EMR, and Lambda.

Deploy high value, high performance datasets in Snowflake.

Creation and support of real-time data pipelines built on AWS technologies including Glue, S3, Lambda, EMR, EventBridge, Athena, Kinesis, and IoT Core.

Embed quality and intelligent reporting capabilities into data pipelines including detection of anomalies and changes in trends with meaningful alerts and statistics.

Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.

Collaborate with data scientists and other tech teams to implement advanced analytics algorithms into our data pipelines that exploit our rich datasets for statistical analysis, prediction, clustering, and machine learning.

Help continually improve automation and simplifying data as a service.

PLEASE NOTE: Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This includes, but is not limited to, OPT, CPT, and H-1B visa holders.

Degree in computer science, information science, engineering, mathematics, or related technical discipline.

8+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets.

Strong experience with data integration (ETL/ELT) concepts.