Job Description
At MultiPlan, we pride ourselves on being a dynamic team of innovative professionals. Our purpose is simple - we striveto bend the cost curve in healthcare for all. Our dedication to service excellence extends to all of our stakeholders - internal and external - driving us to consistently exceed expectations. We are intentionally bold, we foster innovation, we nurture accountability, we champion diversity, and empower each other to illuminate our collective potential.
Be part of our amazing transformational journey as we optimize the opportunity towards becoming a leading technology, data, and innovation voice in healthcare. Onward and upward!!!
This role will be part of the team responsible for developing and deploying Engineering and Integration solutions. Primary responsibility will be to work closely with the Data Architects and Machine Learning Team to implement data solutions for the organization using Python, Java, Kafka and other big data solutions, creating technical specification documents and test plans. Also provide support for the data solutions across the enterprise.
JOB ROLES AND RESPONSIBILITIES:
1.) Understand business processes and how they are modeled in various systems
2.) Work with business users, technology teams, and executives to understand their data needs to create innovative solutions to fulfil them
3.) Design, organize, and implement data structures, workflows, and integrations between enterprise platforms to ensure the accurate and timely execution of business processes.
4.) Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity.
5.) Guiding decisions and establishing best practices on data integration/engineering, as well as the future of our data infrastructure
6.) Managing and improving the performance of our database, queries, tools, and solutions
7.) Creating and maintaining data warehouse, databases, tables, SQL queries, and ingestion pipelines to power reports(Tableau), dashboards, predictive models, and downstream analysis
8.) Writing complex and efficient queries to transform raw data sources into easily accessible models for our teams and reporting platforms
9.) Prepare data for predictive and prescriptive modeling
10.) Identify and analyze data patterns
11.) Identify ways to improve data reliability, efficiency and quality
12.) Work with analytics, data science, and wider engineering teams to help with automating data analysis and visualization needs, advise on transformation processes to populate data models, and explore ways to design and develop data infrastructure
13.) Document high and low level technical design
14.) Draw performance reports and strategic proposals from analyses results for senior data science leadership
15.) Collaborate, coordinate, and communicate across disciplines and departments.
16.) Ensure compliance with HIPAA regulations and requirements.
17.) Demonstrate Company's Core Competencies and values held within.
18.) Please note due to the exposure of PHI sensitive data -- this role is considered to be a High Risk and privileged role.
Requirements
JOB REQUIREMENTS (Education, Experience, and Training):
• 5+ years' of relevant experience within data engineering.Minimum of 3 years of experience with OOP, SQL, schema designing, data modeling, designing, building, and maintaining data processing systems.
• Strong experience with advanced analytics tools for Object-Oriented/object function scripting using languages such as Scala, Java, and others.Big Data Development experience using Hive, Presto, Spark is preferred.
• Database development experience, building ETL pipelines using SQL and experience with a variety of relational, NoSQL oriented databases like Hadoop, MongoDB, Cassandra.
• Extensive experience in triaging data issues, analyzing end-to-end data pipelines and working with business users in resolving issues.
• Experience in working with data governance/data quality and data security teams and specifically data stewards and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification.
• Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines.
• Exposure to containerization using Docker, Kubernetes etc.
• Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
• Excellent communication skills (verbal, listening and written)
• Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
• Strong attention to detail when identifying data relationships, trends, and anomalies.
• Thinking through long-term impacts of key design decisions and handling failure scenarios.
• Ability to work with both IT and business in integrating
Location: Anywhere
Posted: Sept. 13, 2024, 9:19 a.m.
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