Computer and Information Systems Manager

Fox•Los Angeles, CA

1d•Remote

About The Position

Fox Cable Network Services, LLC seeks a Computer and Information Systems Manager (Manager, Data Engineering), responsible for designing, developing, and maintaining comprehensive Data Lake and warehouse solutions. Tackle challenges that come with complex large-scale data having different streams of data sources. Specific duties include: 1) Lead the design, development, and implementation of data architectures, data pipelines, and data systems. 2) Manage a team of 3-5 data engineers and provide technical guidance and mentorship. 3) Build scalable data infrastructure and understand distributed systems concepts from a data storage and compute perspective. 4) Ensure the accuracy and availability of data to customers and understand how technical decisions can impact the business’s analytics and reporting. 5) Collaborate with cross-functional teams, business partners, stakeholders including senior leadership to understand business requirements, promote best practice and trade-offs, and to provide solutions that meet the organization's goals. 6) Develop, democratize and maintain Data as an asset. 7) Optimize data processes for efficiency, reliability, and scalability. 8) Act as a Subject Matter Expert to the organization for end-to-end data pipeline. 9) Ensure quality by performing root cause analysis and troubleshooting of defects. 10) Stay current with industry trends and advancements in Data Engineering. Telecommuting permitted from any location in the U.S.

Requirements

Requires a Bachelor’s degree in Computer Science, Computer Engineering or related field, plus two (2) years of data engineering or related experience executing multiple large data analytics and engineering projects.
In lieu of Bachelor’s degree in Computer Science, Computer Engineering or related field, plus two (2) years of data engineering or related experience executing multiple large data analytics and engineering projects, will accept four (4) years of data engineering or related experience executing multiple large data analytics and engineering projects.
Experience must include two (2) years of experience designing and developing Platform Architecture and ETL/Data pipelines; developing frameworks and reusable components for AWS cloud data migration and integration; analyzing and capturing batch, streaming and near real-time data (ETL) requirements for Enterprise Data Lake and Data Warehouse; and working with various stakeholders on requirement gathering, defining project scope, roadmaps and short and long-term strategic goals.
Programming languages such as Python or Java
pySpark or Scala
AWS Redshift, Athena, Spectrum, DynamoDB and RDS
Amazon Web Services including EC2, Elastic Map Reduce (EMR), Glue, Lambda, Kinesis, IAM, ECS, S3, API Gateway, Kinesis and Kafka
Agile Methodology, Software Development Life Cycle, Test Strategy and Performance Tuning
Databricks, PL/SQL, Shell scripting, Tableau and Looker
Jira, Bitbucket, Confluence and Git

Responsibilities

Lead the design, development, and implementation of data architectures, data pipelines, and data systems.
Manage a team of 3-5 data engineers and provide technical guidance and mentorship.
Build scalable data infrastructure and understand distributed systems concepts from a data storage and compute perspective.
Ensure the accuracy and availability of data to customers and understand how technical decisions can impact the business’s analytics and reporting.
Collaborate with cross-functional teams, business partners, stakeholders including senior leadership to understand business requirements, promote best practice and trade-offs, and to provide solutions that meet the organization's goals.
Develop, democratize and maintain Data as an asset.
Optimize data processes for efficiency, reliability, and scalability.
Act as a Subject Matter Expert to the organization for end-to-end data pipeline.
Ensure quality by performing root cause analysis and troubleshooting of defects.
Stay current with industry trends and advancements in Data Engineering.