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Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together.

Optum Advisory Services (OAS) is seeking an Associate Director of Data Engineering with extensive health care experience to design, develop, implement and manage cross-domain, modular, flexible, scalable, secure, reliable and quality data solutions that transform data to support analytics and insight generation for our clients. The Associate Director of Data Engineering will evolve the delivery of data in a systematic method and will support a wide variety of analytical products and services. This role will support development and maintenance activities to ensure that we deliver data with high quality for our users, applications, and services and to understand customer needs. The Associate Director of Data Engineering will perform and oversee a wide variety of activities that include but are not limited to analysis, design, coding, engineering, testing, debugging, standardization, tools selection, documentation, research, maintenance, development, operations and delivery. The Associate Director of Data Engineering will be responsible for building quality and efficiency into every output.

Primary Responsibilities:

• Data Solutions

• Accountable for the full data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment and maintenance of data solutions

• Design, develop, implement and run data solutions that improve data efficiency, reliability, and value

• Establish ETL architecture and data architecture best practices for managing complex data sets within a given domain

• Implement solutions and standards for data acquisition, transformation, storage, and aggregation that solve current challenges and reduce the risk of future challenges

• Leverage knowledge of various data management technologies to drive enterprise direction

• Design and builds data management frameworks for data quality, error handling, audit/balance/control and reusable data transformation structures that accommodate all health care domains

• Effectively create elegant data solutions that address business requirements and other constraints

• Apply a comprehensive enterprise view to the build of data models and broad data management

• Recommend opportunities to expand business value from well managed data

• Engage with other architecture and engineering teams on planning data systems and designing well-architected data platforms

• Support the design and implementation of a modern data framework that facilitates business intelligence reporting and advanced analytics, including machine learning models

• Scalability, Security, & Quality Assurance

• Eliminate unwarranted complexity and unneeded interdependencies

• Detect data quality issues, identify root causes, implement fixes, and design data audits to capture issues

• Include instrumentation in the development process so that data pipelines can be monitored, and problems can be detected quickly and proactively before they result into user visible outages or data quality issues

• Build processes and diagnostics tools to troubleshoot, maintain and optimize solutions and respond to customer and production issues

• Continuously promote technical debt reduction, process transformation, and overall optimization

• Create and enforce standards for high quality documentation of data definitions, transformations, and processes to ensure data transparency, governance, and security

• Ensure that all solutions meet the business needs and requirements for security, scalability, and reliability

• Leverage and contribute to broader Optum standards, best practices, and investments in data orchestration, data architecture, and data modeling to maximize economies of scale

• Build instrumentation and analytics that illustrate the business value of investment in data engineering maintenance and optimization efforts including both tooling and talent

• Talent Leadership

• Hire, Lead, mentor, and manage data architects, data analysts, data engineers, tool admins, DBAs and empower them to deliver the best possible outcomes from their work

• Embrace continuous learning of engineering practices to promote adoption of industry best practices and technology, including DevOps, Cloud and Agile thinking

• Instill insight and knowledge regarding data technologies, including big data, streaming, and data storage, into the broader data engineering teams

• Provide feedback and review the work of others to ensure the value of deliverables

• Facilitate proactive research of emerging technologies and develop strategic recommendations that would expand value or improve efficiencies

• Craft career development plans and conduct regular reviews to both gather and provide feedback

• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor’s Degree (preferably in information technology, engineering, math, computer science, analytics, or other related field)

• 10+ years of combined experience in data engineering, ingestion, normalization, alignment, transformation, aggregation, modeling, and storage

• 10+ years of experience in data warehouse and data mart build using normalized or dimensional or data vault methodologies

• 7+ years of experience managing complex data projects and programs

• 7+ years of experience in designing ETL/ELT solutions using tools like Informatica, DataStage, Health Catalyst, SSIS , PL/SQL, T-SQL, Azure Data Factory, Data Bricks etc.

• 7+ years of experience managing concurrent data & analytics initiatives with minimal guidance

• 7+ years of experience building, mentoring, and managing high performing teams or directing the work of others

• 5+ years of experience in managing large healthcare data assets using SQL or Python or Spark SQL or other similar querying/coding language

• 2+ years of experience in data masking and non-production environment setup to support testing of various data products

• Willingness to travel up to 10%

Preferred Qualifications:

• Advanced degrees or certifications (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)

• Solid experience with multiple EPIC modules or components: Caboodle development, Clarity data models, Epic Care Everywhere, Grand Central, Healthy Planet, Prelude, Resolute, Reporting Workbench, Slicer Dicer , Data Courier

• Depth of experience and proven track record creating and maintaining sophisticated data frameworks for healthcare organizations

• Experience working in Azure, AWS, or google cloud ecosystems

• Experience working with Amazon Redshift, Amazon S3, Hadoop HDFS, Azure Blob, or similar big data storage and management components

• Experience working with Spark, MapReduce, Data Bricks or related processing techniques

• Experience building & supporting data pipelines that power analytical content within common reporting and business intelligence platforms (e.g. Power BI, Qlik, Tableau, MicroStrategy, etc.)

• Experience working with large data pipelines that transfer and process data using Spark, Scala, Python, Apache Kafka, etc.

• Experience justifying need for investments in data management to business leaders

• Experience contributing to cross-functional efforts, with proven success in creating healthcare insights

• Experience and credibility interacting with analytics and technology leadership

• Proven willingness to define best practices, share knowledge, and improve the collective work of the team

• Proven ability to support multiple client initiatives or projects

• Proven ability to communicate complex concepts verbally and in writing

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.