Data Engineer (AWS) - Assistant Manager

Job description

**Summary** **Position Summary** **L40 -** **Data Analytics Engineer** **–** **II** **Data Engineer should be a passionate, innovative, results-oriented predictive analytics leader with a deep commitment to success to be a part of our technology delivery processes that support the finance, talent (HR), risk management and IT service areas.This role requires specialized skills in predictive analytics for discovering data-driven insights that are actionable and transformative for restructuring strategies and operations to drive business value.** **Work you will do** **The Data Scientist Specialist will be responsible for recommending SAP HANA-based application architecture, service architecture, and technical design solutions for high performance and scalability in a distributed, multi-tier and cross-platform environment. This role requires extensive experience in designing and deploying predictive models that support business applications.The specialist will create benchmark tests, design for scalability and performance, and implement on large-scale systems.This includes an expectation for thought leadership on projects requiring requirements gathering, ETL capabilities, data modeling and interpretation, QA testing, and visualization design.** **Outcome-Driven Accountability** - Collaborate with business and IT leaders to develop and refine ideas for integrating predictive and prescriptive analytics within business processes, ensuring measurable customer and business outcomes. - Decompose complex business problems into manageable components, facilitating the use of multiple analytic modeling methods for holistic and valuable solutions. - Develop and refine prototypes and proofs of concepts, presenting results to business and IT leaders, and demonstrating the impact on customer needs and business outcomes. **Technical Leadership and Advocacy** - Engage in data analysis, generating and testing hypotheses, preparing and analyzing historical data, identifying patterns, and applying statistical methods to formulate solutions that deliver high-quality outcomes. - Develop project plans, including resource needs and task dependencies, to meet project deliverables with a focus on incremental and iterative delivery. **Engineering Craftsmanship** - Participate in defining project scope, objectives, and quality controls for new projects, ensuring alignment with customer-centric engineering principles. - Present and communicate project deliverable results, emphasizing the value delivered to customers and the business. **Customer-Centric Engineering** - Assist in recruiting and mentoring team members, fostering a culture of engineering craftsmanship and continuous learning. **Incremental and Iterative Delivery** - Stay abreast of changes in technology, leading new technology evaluations for predictive and statistical analytics, and advocating for innovative, lean, and feasible solutions. **Key Responsibilities** - Create plans as proof-of-concept and presenting related results including prototypes to business and IT leaders. - Develop project plans that include specification of resource needs and task dependencies to meet project deliverables. - Direct data preparation planning effort and ETL procedure development and testing. - Design and interpreting analytical models to discover data-driven insights that are actionable and transformative for restructuring strategies and operations to drive business value. - Evaluate the performance of LLM models. This may involve measuring the models' accuracy on our tuned datasets. - Design and deploy predictive and prescriptive models that may include LLM models to support business applications. Ability to package the model, create REST APIs, and deploy on cloud environments. - Contribute to thought leadership initiatives, hackathons, internal innovation initiatives to promote PxE's reputation in predictive and generative analytics. - Stay updated with technological advancements and participate in evaluations of new technologies for predictive, statistical, and generative analytics. - Utilize Databricks for scalable data engineering, collaborative data science, and machine learning workflows. - Leverage Dataiku for data science and analytics platform capabilities, including data preparation, visualization, and model deployment. - Integrate Generative AI technologies to create innovative data-driven solutions and enhance analytics capabilities. Education: - Advanced degree in quantitative discipline (Statistics, Math, Computer Science, Engineering) or relevant experience. Qualifications: - Proven track record of leveraging data analytic methods and experience with very large datasets to create data-driven insights thru predictive and prescriptive analytic models. - Extensive knowledge of supervised and unsupervised analytic modeling techniques such as linear and logistic regression, support vector machines, decision trees / random forests, Naïve-Bayesian, neural networks, association rules, text mining, and k-nearest neighbors among other clustering models. - 7+ years of experience with data analysis software for large scale analysis of structured and unstructured data. - 7+ years of experience with data mining, statistical modeling tools and underlying algorithms. - Experience leading project teams. - Ability to communicate complex quantitative analysis in concise and actionable manner. - Proven ability to work independently and manage multiple task assignments. - Strong oral and written communication skills, including presentation skills. - Strong problem solving and troubleshooting skills with the ability to exercise good judgment. - Strong time management and multi-tasking skills that have been demonstrated by track-record of working on multiple projects and cross-functional teams with staggered deadlines. - Aptitude with Exploratory Data Analysis of large, complex datasets to arrive at useful insights and hypotheses. - Working knowle