Design and Lead large scale Data Engineer/Architect solutions. This role will act as the lead to large initiatives and will communicate with users of all levels across the organization.
The data architect and the data engineer may acquire same or very similar expertise in Database Architecture over time, but they use this knowledge differently. While data architects provide knowledge and guidance in handling disparate data sources from varied databases, the data engineers take the architect’s vision to build and maintain the Data Architecture for the enterprise data professionals.
Data Engineering develops, constructs and maintains large-scale data processing systems that collects data from variety of structured and unstructured data sources, stores data in a scale-out data lake and prepares the data using ELT (Extract, Load, Transform) techniques in preparation for the data science data exploration and analytic modeling:
- Collects the data from a variety of traditional and non-traditional sources, stores it in a data repository, cleanses and integrates the data (data prep) for analysis.
- Designers, builders and managers of the information and big data infrastructure. They co-develop the architecture that helps analyze and process data that the organization required and further optimize those systems to perform smoothly.
- Evaluates, compares and improves the different approaches including design patterns innovation, data lifecycle design, data ontology alignment, annotated datasets, and elastic search approaches.
- Prepares the data for the data scientist exploration and discovery process. For example, we have data containing 30 attributes where two attributes are used to compute another attribute (for example, an index), and that computed feature is used for further analysis. In this way, the data could be changed according to the requirement of the applied model.
- “Wrangles” the data, sometimes called data munging or data schmarzing (just checking to see if you’re reading) which transforms, maps and “munges the raw data using algorithms (e.g. sorting, parsing) into predefined data structures, and depositing the results into a data lake for the downstream analytics.
Much of the data engineering work tends to be domain specific (requires an understanding of the unique meaning of the data given the business or operational problem being solved) and involves the business stakeholders
The Data Engineer(Architect) job family is responsible for working with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies. Includes utilizing statistical models/algorithms and data visualization techniques.
Job Duties and Responsibilities
- Oversee and direct efforts to identify information and technology solutions that enable business needs and strategies.
- Apply business knowledge and experience to effectively advise others on technology as an enabler.
- Lead efforts to analyze IT industry and market trends and determine potential impacts.
- Develop concepts and constructs necessary to create technology-enabled business systems.
- Influence technology direction.
- Provides thought leadership and execution to large complex efforts.
- Utilize breadth of technical understanding and dive deep when necessary.
- Consult on and manage initiatives to ensure alignment across multiple business and IT areas.
- Proactively mitigate risks across multiple assets, information domains, technologies & platforms.
- Provide leadership, mentoring and technical guidance to others to drive initiatives.
- Facilitate communications that involve obtaining cooperation and agreement on issues that may be complex or controversial.
- Utilize negotiation and persuasion to come to agreement and to effectively form partnerships.
- Act as a change agent to continuously improve and move the organization forward.
- Accountable to provide leadership to successfully deliver the right results on initiatives in a timely and effective manner.
- Direct the work of others to lead initiatives that cross multiple assets, technologies, platforms, departments and vendors.
- Ability to work within a diverse team of skillsets and experience levels to deliver results.
Required Job Qualifications
- Bachelor’s degree or equivalent experience in MIS, Computer Science, Mathematics, Business, or related field
- 8+ years of experience in Technology related field including 3+ years prior lead experience
- Expert knowledge of Predictive Analytics, Statistical modeling, advanced mathematics, Data integration concepts, Business Intelligence and Data Warehousing and implementing large systems
- Strong organizational, analytical and critical thinking and leadership skills
Thrivent provides Equal Employment Opportunity (EEO) without regard to race, religion, color, sex , gender identity, sexual orientation, pregnancy, national origin, age, disability, marital status, citizenship status, military or veteran status, genetic information, or any other status protected by applicable local, state , or federal law. This policy applies to all employees and job applicants.
Thrivent is committed to providing reasonable accommodation to individuals with disabilities. If you need a reasonable accommodation , please let us know by sending an email to email@example.com or call 800-847-4836 and request Human Resources.