Senior Big Data Engineer - (Person360 & MDM)

at  Highmark Health

JOB SUMMARY

We are on a mission to deliver remarkable health experiences, freeing people to be their best. This requires an advanced 360 person-centered approach to deliver the right message, guidance, care, outcome, and experiences, all at the right time. This Sr Engineering role on the team will help lead us towards the combined digital and data transformation, modernizing from core Master Data Management (MDM) platforms and processes towards more open and forward oriented platforms, patterns, and architectures. On an ongoing basis, you will collaborate and/or lead various technical engagements to scope, deliver, and support core operational systems focusing on delivering a Person-360 ecosystem. These patterns and platforms will serve as foundational to an enterprise 360 approach, improving individuals’ experiences and business outcomes. Working in a distributed team, you can influence and lead both technical and non-technical cross-functional team members, building trust and momentum with stakeholders, prioritizing outcomes over activity. You will be pragmatic in modernizing technology by pairing innovation and transformation with business requests and customer experiences.

POSITION TYPE

Office-based
Teaches / trains others regularly
Rarely
Travel regularly from the office to various work sites or from site-to-site
Does Not Apply
Works primarily out-of-the office selling products/services (sales employees)
Never
Physical work site required
No
Lifting: up to 10 pounds
Constantly
Lifting: 10 to 25 pounds
Occasionally
Lifting: 25 to 50 pounds
Rarely
Disclaimer: The job description has been designed to indicate the general nature and essential duties and responsibilities of work performed by employees within this job title. It may not contain a comprehensive inventory of all duties, responsibilities, and qualifications required of employees to do this job.
Compliance Requirement : This job adheres to the ethical and legal standards and behavioral expectations as set forth in the code of business conduct and company policies.
As a component of job responsibilities, employees may have access to covered information, cardholder data, or other confidential customer information that must be protected at all times. In connection with this, all employees must comply with both the Health Insurance Portability Accountability Act of 1996 (HIPAA) as described in the Notice of Privacy Practices and Privacy Policies and Procedures as well as all data security guidelines established within the Company’s Handbook of Privacy Policies and Practices and Information Security Policy.
Furthermore, it is every employee’s responsibility to comply with the company’s Code of Business Conduct. This includes but is not limited to adherence to applicable federal and state laws, rules, and regulations as well as company policies and training requirements.

• 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. Create high performance cloud and big data systems to be used with operational and analytic applications.
• 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, design, code, test, implement, and maintain scalable and extensible frameworks that support data engineering services.
• Align with security, data governance and data quality programs by driving 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.
• Develop, optimize and/or maintain machine learning and AI engineering processes (MLOps) that are deployed to cloud or big data environments. These may be based on prototypes built by data scientists or capability frameworks implemented to allow data scientists to build efficiently in production environments.
• Develop tasks across multiple projects with limited need for guidance. This includes providing guidance and education to Intermediate and Junior contributors within team. Manage relationships with customers of the function. Attend meetings with customers on a stand-alone basis or with team as needed.
• Establish standards and patters for high performance data ingestion, transformation, and delivery of data analytic needs. Keep current with Big Data technologies in order to recommend best tools in order to perform current and future work
• Other duties as assigned or requested.