Senior Data Engineer

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. We are currently seeking a Senior Data Engineer to be part of a global team and function in a lead developer role. You will perform analysis, design and development of data processing ETL job streams to support the data warehouses, data marts and other data stores in support of the Optum business. You will do hands-on development and testing work as part of a scrum team that is global in nature. The primary technology stack will be Azure Databricks environment, with Delta Lake, Airflow, Python components and a Snowflake data store. You will work closely with external and internal stakeholders to design solutions to solve problems and resolve issues. Functions may include database architecture, engineering, design, optimization, security, and administration; as well as data modeling, big data development, Extract, Transform, and Load (ETL) development, storage engineering, data warehousing, data provisioning and other similar roles. Responsibilities may include Platform-as-a-Service and Cloud solution with a focus on data stores and associated eco systems. Duties may include management of design services, providing sizing and configuration assistance, ensuring strict data quality, and performing needs assessments. Analyzes current business practices, processes and procedures as well as identifying future business opportunities for leveraging data storage and retrieval system capabilities. Manages relationships with software and hardware vendors to understand the potential architectural impact of different vendor strategies and data acquisition. May design schemas, write SQL or other data markup scripting and helps to support development of Analytics and Applications that build on top of data. Selects, develops and evaluates personnel to ensure the efficient operation of the function.

As Data Engineer, you will evaluate, design, develop, maintain and test Big Data solutions. You will be involved in data engineering activities like creating pipelines/ workflows for source to target mappings Responsible for data ingestion from files, streams and databases. Process the data using Azure Databricks, Python, SQL Design and development of ETL data flows using Azure Databricks ecosystem components. Lead the development of large-scale, high-speed, and low-latency data solutions in the areas of large-scale data manipulation, long-term data storage, data warehousing, low-latency retrieval systems, real-time reporting and analytics data applications, ad-hoc analytics. Performance tune long running jobs. Develop programs in Python and SQL as part of data cleaning and processing. Develop efficient code for multiple use cases leveraging Python and Big Data technologies on the Azure platform in an optimal manner Build and maintain CI/CD pipelines using Github Actions Identify and build Ai-powered solutions. Document architecture and design components. Be able to communicate these to other engineers on the team. Guide and mentor junior engineers Follow DevOps practices to automate the data pipelines Basic, structured, standard approach to work. 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