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Data Engineer (Epic, Cerner, Databricks, Azure) | TELECOMMUTE
- United States
- United States
À propos
Hours:
9am-5pm EST additional overtime and weekends on as needed basis
Team:
Architects and 2 Data engineers along with India Team members supporting JMH
Client 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.
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 Ideal Background:
Healthcare background including Azure ADF and Databricks background.
Required:
Bachelor's Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field) Minimum of 5+ years of combined experience in data engineering, ingestion, normalization, transformation, aggregation, structuring, and storage Minimum of 5+ years of combined experience working with industry standard relational, dimensional or non-relational data storage systems Minimum of 5+ years of experience in designing ETL/ELT solutions using tools like Informatica, DataStage, SSIS , PL/SQL, T-SQL, etc. Minimum of 5+ years of experience in managing data assets using SQL, Python, Scala, VB.NET or other similar querying/coding language Minimum of 3+ years of experience working with healthcare data or data to support healthcare organizations Preferred:
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 Minimum of 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 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 Experience and credibility interacting with analytics and technology leadership teams Willingness to support limited travel up to 10%
Compétences linguistiques
- English
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