Job Description

Job Title: Big Data Engineer – USC only

Location: 100% Remote

Schedule: Monday – Friday normal business hours

Job Description:

This job is responsible for designing and engineering data solutions for the enterprise and, working closely with business, analytic and IT stakeholders, assists with the development and maintenance of these solutions. This includes coding data ingestion pipelines, transformations and delivery programs/logic for people and systems to access data for operational and/or analytic needs. Duties include but are not limited to the coding, testing, and implementation of ingestion and extraction pipelines, transformation and cleansing processes, and processes that load and curate data in conformed, fit-for-purpose data structures.

The incumbent is expected to partner with others throughout the organization (including other engineers, architects, analysts, data scientists, and non-technical audiences) in their daily work. The incumbent will work with cross-functional teams to deliver and maintain data products and capabilities that support and enable strategies at business unit and enterprise levels.

The incumbent is expected to utilize technologies such as, but not limited to: Google Cloud Platform, Hadoop, Hive, NoSQL, Kafka, Spark, Python, Linux shell scripting, SAS, Teradata, Oracle, and Informatica.

Responsibilities:

• In partnership with other business, platform, technology, and analytic teams across the enterprise, design, build and maintain well-engineered data solutions in a variety of environments, including traditional data warehouses, Big Data solutions, and cloud-oriented platforms.
• Work with internal and external platforms and systems to connect and align on data sourcing, flow, structure, and subject matter expertise. Work with business stakeholders and strategic partners to implement and support operational and analytic platforms. This may include products purchased by the organization that must be ingested or modeled/derived data maintained by enterprise platforms and data consumers.
• Working across multiple, disparate systems and platforms, code, test, implement, and maintain scalable and extensible frameworks that support data engineering services.
• Align with security, data governance and data quality programs by contributing to assigned components of metadata management, data quality management, and the application of business rules. Develop and maintain associated data engineering processes and participate in required operating procedures as part of the enterprise’s overall information management activities. Includes data cleansing, standardization, technical metadata documentation, and the de-identification and/or tokenization of data.
• Maintain machine learning and AI engineering processes (MLOps) that are deployed to cloud or big data environments.
• Responsible for delivery of assigned projects, this may include providing guidance to Junior contributors within team. Will attend meetings with customers as needed.
• Assist with the establishment of standards and patterns for high performance data ingestion, transformation, and delivery. Keep current with cloud, big data, and data science technologies and be able to recommend and use best tools to perform current and future work.
• Other duties as assigned or requested.

Required Qualifications:

• Bachelor's Degree in Software Engineering, Information Systems, Computer Science, Data Science or related field
• 3 years of Data platform development, data engineering, software development, or data science
• 1 year of Big data or cloud data platform
• SQL
• Data Warehousing
• Problem-Solving
• Communication Skills
• Analytical Skills

Preferred Qualifications:

• Master's Degree Software Engineering, Information Systems, Computer Science, Data
• Science or related field
• 1 year of Google Cloud Platform, AWS, Azure or other cloud platform
• 1 year of Spark or Python
• 1 year of Data science, AI & machine learning engineering
• 1 year Healthcare Industry
• 1 year of Database Administration