Senior Data Engineering Analyst

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 inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Optum is seeking a Data Engineer with health care experience to 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 Data Engineer will implement, test, deploy, monitor, and maintain the delivery of data in a systematic method and will support a wide variety of analytical needs for our customers. The Director of Data Engineering will also partner with the broader OAS Analytics organization to harness the power of client data to facilitate analytical insight and will be responsible for building quality and efficiency into every project.

Primary Responsibilities:

Support the full data engineering lifecycle including research, proof of concepts, design, development, testing, deployment, and maintenance of data management solutions

Utilize knowledge of various data management technologies to drive data engineering projects

Lead data acquisition efforts to gather data from various structured or semi-structured source systems of record to hydrate client data warehouse and power analytics across numerous health care domains

Leverage combination of ETL/ELT methodologies to pull complex relational and dimensional data to support loading DataMart's and reporting aggregates

Eliminate unwarranted complexity and unneeded interdependencies

Detect data quality issues, identify root causes, implement fixes, and manage data audits to mitigate data challenges

Implement, modify, and maintain data integration efforts that improve data efficiency, reliability, and value

Leverage and facilitate the evolution of best practices for data acquisition, transformation, storage, and aggregation that solve current challenges and reduce the risk of future challenges

Effectively create data transformations that address business requirements and other constraints

Partner with the broader analytics organization to make recommendations for changes to data systems and the architecture of data platforms

Support the implementation of a modern data framework that facilitates business intelligence reporting and advanced analytics

Prepare high level design documents and detailed technical design documents with best practices to enable efficient data ingestion, transformation and data movement

Leverage DevOps tools to enable code versioning and code deployment

Leverage data pipeline monitoring tools to detect data integrity issues before they result into user visible outages or data quality issues

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

Continuously support technical debt reduction, process transformation, and overall optimization

Leverage and contribute to the evolution of 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

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 regard 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

AI User Responsibilities:

Leverage enterprise-approved AI tools to enhance productivity and innovation by streamlining workflows and automating repetitive tasks. Evaluate emerging trends to drive continuous improvement and strategic innovation.

Required Qualifications:

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

3+ years of experience in Microsoft Azure Cloud, Azure Data Factory, Data Bricks, Spark/ Scala / Python , ADO

3+ years of combined experience in data engineering, ingestion, normalization, transformation, aggregation, structuring, and storage

3+ years of combined experience working with industry standard relational, dimensional or non-relational data storage systems

2+ years of experience in designing ETL/ELT solutions

3+ years of experience in managing data assets using SQL, Python, Scala, VB.NET or other similar querying/coding language

2+ years of experience working with healthcare data or data to support healthcare organizations

Preferred Qualifications:

5+ years of experience in creating Source to Target Mappings and ETL design for integration of new/modified data streams into the data warehouse/data marts

2+ years of experience with Epic Clarity and/or Caboodle data models or with Cerner Millennium / HealthEintent and experience using Cerner CCL

2+ years of experience working with Health Catalyst product offerings, including data warehousing solutions, knowledgebase, and analytics solutions

Epic certifications in one or more of the following modules: Caboodle, EpicCare, Grand Central, Healthy Planet, HIM, Prelude, Resolute, Tapestry, or Reporting Workbench

Experience in Unix or Powershell or other batch scripting languages

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

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

Experience supporting analytical capabilities inclusive of reporting, dashboards, extracts, BI tools, analytical web applications and other similar products

Experience and credibility interacting with analytics and technology leadership teams

Exposure to Azure, AWS, or google cloud ecosystems

Exposure to Amazon Redshift, Amazon S3, Hadoop HDFS, Azure Blob, or similar big data storage and management components

Desire to continuously learn and seek new options and approaches to business challenges

A willingness to leverage best practices, share knowledge, and improve the collective work of the team

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

Ability to effectively communicate concepts verbally and in writing

Willingness to support limited travel up to 10%

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.

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