NISC is looking to optimize their data and data pipeline architecture to support their application experts, software developers, database architects, and data analysts, and to ensure optimal data delivery architecture is consistent throughout ongoing projects.
Requirements
- Experience building and optimizing data pipelines, architectures, and data sets.
- Experience with AWS: Lambda, S3, SQS, SNS, CloudWatch, etc.
- Experience with Databricks and Delta Lake.
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Oracle, Postgres Cassandra, and DynamoDb.
- Experience with data pipeline and workflow management tools: Hevo Data, Airflow, etc.
- Experience with object-oriented languages: Java, Scala.
Responsibilities
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Design and build optimal data pipelines from a wide variety of data sources using AWS technologies.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing a unified data stream.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Create and maintain a culture of engagement and one that is conducive of NISC’s Statement of Shared Values.
- Commitment to NISC’s Statement of Shared Values.
Other
- Bachelor’s degree in Computer Science, Statistics, Informatics, Information Systems or similar discipline, preferred.
- Certification in Database Administration, along with relevant experience in lieu of 4-year degree.
- Strong verbal and written communication skills.
- Ability to demonstrate composure and think analytically in high pressure situations.
- Commitment to NISC’s Statement of Shared Values.
