ARC is looking for a Senior Big Data Engineer to work on a major implementation we are currently engaged on in Jacksonville, FL. This is a long term (6-12 months) position. Preference would be to be onsite in Jacksonville, but remote work with periodic site visits will be considered.
- Design and code data pipeline features and data processing jobs that encompass innovative business analytics
- Ensure smooth ongoing operations of data platform with high availability while making continuous improvements
- Help engineering teams across the organization to understand and consume the data sets and platform for improved decision-making and analytics
- Advance the data architecture and platform and ensure alignment to architectural tenets
- Design, implement and maintain data models including partitioning and bucketing strategies
- Collaborate with the Data Science team in order to refine and implement algorithms aligned with business strategy
- Participate in the design and development of services, architecture, and performance standards
- Devise partitioning and bucketing strategies
BS in Computer Science, Mathematics, or equivalent degree with a combined 7+ years of software development and demonstrated experience working with large data sets.
The ideal candidate will also have:
- Hands-on coding experience in programming languages such as Java, Python, Scala
- Experience designing and delivering large scale, 24-7, mission-critical data pipelines and features using modern big data architectures
- Stream processing services such as Kafka, AWS Kinesis, Apache Storm, Spark Streaming.
- Experience in any big data technologies - Hadoop, EMR, Amazon Redshift, AWS DynamoDB, or advanced analytics tools will be plus
- Demonstrated experience working in large-scale data environments which included real-time and batch processing requirements
- Strong understanding of ETL processing with large data stores
- Strong data modeling skills (relational, dimensional and flattened)
- Strong analytical and SQL skills, with attention to detail