Sr Data Engineer

Job Requirements

Under limited direction, responsible for design and implementation of core technologies associated with the organization's data analysis and analytics technical infrastructure. As a core member of a high-performance team, ensure data pipelines are consistently and reliably maintained and analytics capabilities are delivered at an optimum level, helping the organization identify insights from a large number of diverse datasets.

Principal Responsibilities And Tasks

• Ensure analytics infrastructure and associated systems meet business requirements and industry best practices.
• Gather and process raw data from multiple disparate sources (including writing scripts, calling APIs, write SQL queries, etc.) into a form suitable for analysis.
• Gathers, analyzes, documents and translates application requirements into data models.
• Builds data models.
• Enables big data, batch and real-time analytical processing solutions leveraging emerging technologies.
• Researches and proposes opportunities for data acquisition and new uses for existing data.
• Codes, tests, and documents new or modified data systems to create robust and scalable applications for analytics.
• Translates complex functional and technical requirements into detailed architecture, design and high performance software.
• Builds and architects next-generation Big Data analytics framework
• Expands and grows data platform capabilities to solve new data problems and challenges.
• Creates data flow diagrams for business systems.
• Builds automation tools; ensures all automated processes preserve data by managing the alignment of data availability and integration processes.
• Performs technology and product research to better define requirements, resolve important issues and improve the overall capability of the technology stack.
• Contributes to the design and direction of enterprise-wide data architecture as well as design documentation deliverables.
• Supports standardization of documentation and the adoption of standards and practices related to data and applications.
• Develops Relational Data Models, Dimensional Data Models, Data Dictionary and Metadata.
• Develop data set processes for data mining and production.
• Works both independently and in collaboration with our data integration developers, data scientists, designs and builds high-performance algorithms, prototypes, predictive models and proof of concepts.
• Works closely with our developer team to integrate innovative algorithms into our production systems.
• Supports business decisions with ad hoc analysis as needed.
• Assesses and provides recommendations on business relevance, appropriate timing and deployment.
• Works well in a high-performance team environment.
• Architects highly scalable distributed systems using non-proprietary tools.

Work Experience

• Bachelor’s Degree in Computer Science, Mathematics, Information Systems, Engineering, Physical Sciences, Life Sciences or closely related field or equivalent related professional experience is required.
• Seven or more (7+) years’ experience designing, implementing and supporting systems in a large scale analytics or data engineering environment containing many disparate application systems and multiple data sources.
• Strong knowledge in programming or scripting languages (e.g., C/C++, Python, Ruby).
• Experience With Agile Or Other Rapid Application Development Methods.
• Experience with object-oriented design, coding and testing patterns as well as experience in engineering software platforms and large-scale data infrastructures.

Knowledge, Skills And Abilities

• Knowledge of data analysis, end user requirements analysis, and business requirements analysis to develop a clear understanding of the business needs and to incorporate these needs into technical solutions.
• Significant knowledge of data modeling and understanding of different data structures and their benefits and limitations under particular use cases.
• Working knowledge of relational, document oriented or object oriented databases, such as PostgreSQL, Oracle, Cache, SQL, MongoDB.
• Deep knowledge in data mining, machine learning or natural language processing.
• Strong programming experience to clean and scrub noisy datasets;
• Experience building algorithms.
• Experience with Hortonworks or the Hadoop ecosystem in general, including HDFS and such tools as Spark, MapReduce, Pig and Hive.
• Experience with Ranger / Atlas and/or Falcon.
• Experience with various messaging systems, such as ActiveMQ or RabbitMQ.
• Experience with Big Data machine learning toolkits, such as Mahout, SparkML or TensorFlow.

Benefits

All your information will be kept confidential according to EEO guidelines. Compensation Pay Range: $57.87 - $92.40

Other Compensation (if applicable)

Review the 2025-2026 UMMS Benefits Guide