The Data Engineer provides leadership, guidance, and hands on development as required for analytic data architecture, conceptual data models, data transformation and consumption, reference data definition, data modeling form, fit, and function for data and data channels, and advanced analytic architectural considerations for data management areas (i.e. data integration, data security, data quality management) as they relate to data science solutions.
Represents business stakeholders for data and analytics requirements and solution design. Focuses on data preparation for analytical consumption; multi source and structured and unstructured. Researches and recommends leading practices and industry trends in analytic data architecture and data modeling.
1) Primary custodian of data analytics architecture, data transformation and consumption strategies for both data mining and data science models / algorithms. Coordinates with Data Governance, IT Data Architecture and Cyber Security to ensure that analytic architectures fit within Business and IT strategies. Provides senior thought leadership and recommendations on data architecture leading practices.
2) Develop and integrate new data management technologies with clear articulation of data sources, data transformation channels, consuming systems, data and visualization models, and integration mechanism for key information objects (master data and transactional data) for high-performance algorithms, prototypes, predictive models, and proof of concepts.
3) Develop and maintain data models including subject area models, conceptual models, CRUD (Create-Read-Update-Delete) data life cycle models, and logical models from a business perspective.
4) Develop and maintain meta data, reference data, and business data dictionary, compliant with data standards, and policies, and emerging industry best standards for data management from a business perspective.
5) Collaborate with Data Scientists to ensure proper data is collected and prepared for analysis. Review and approve data, reporting and analytic functional and non-functional requirements on behalf of the business
6) Maintain functional solution design inventory.
7) Lead and/or support new software or solution evaluations in collaboration with data and analytics team, IT Architects and business unit stakeholders.
8) Integrate, code, and develop data channels including transformation, middleware, and or services to present both data and metadata in a form consumable by algorithms specified by Data Miners and Scientists. Must design and develop with an understanding towards how the data algorithms and models will consume and utilize the data towards prescribed outcomes.
Preferred Special Skills, Knowledge or Qualifications
- Knowledge of applicable federal and state laws, regulations, and standards impacting business unit areas.
- Excellent customer service, organizational, and analytical skills.
- Demonstrated communication skills, both verbal and written. Must be able to work on multiple tasks simultaneously.
•Bachelors' degree in a relevant business or science, information technology or analytics, applied math, statistics, physics or related field and ten (10) years data management or data/IT architecture design role including / emphasizing direct business solutions design and development OR Master¿s degree and eight (8) related experience. In lieu of degree, equivalent combination of education and directly related experience equaling 14 years is required.
•Proficient in data/IT architecture leading practices, data modeling, data integration, CRUD modeling, SQL,
workflows and related tools.
•Proficient in one or more data modeling, and analytical tools.
•Proficient in solutions programming and/or development.
•Programming skill in Python, C/C++, Java, or R. Familiarity with RapidMiner, SAS, SPSS, RStudio, Anaconda, MatLab, Azure, Databricks, ELK, or other data mining platforms.
•Working understanding of Data Lakes, Cloud architectures, transactional data systems and flows, and streaming data sources such as PI.
•Knowledge of statistical analysis, machine learning, data mining, NLP, predictive analytics, text mining and modeling general concepts.
•Proficient in relational and non-relational data systems implementation.
•Experience with scripting, APIs and data source development.
•Experience with data transformations for analytic use including information flow, query execution and optimization, comparative analysis of data stores, logical operations, database and data channel setup / management, data infrastructure design and build.