Data Engineer for Digital Operations -with Advanced Analytics - Positive Work Culture

General Description:
Connected Operations is a part of the larger Customer Experience organization and are at the fore front of the transition to a digital eco system where our interactions with our customers, our partners (dealers) now have more digital footprints. There are some major digital initiatives in the areas of NLP engines including speech to Text for IVR (Interactive Voice Response systems), transition to using Intelligent Bots handling customer queries, using machine learning tools to improve our systems.
We are also responsible to ensure the transactional performance of in-vehicle product services (OnStar services delivered using cellular connection CDMA/LTE such as OnStar Vehicle Diagnostics, Vehicle Health Alerts, Theft Alert Notification, Hands Free Calling, Smart Driver, Turn-by-turn navigation instructions, automatic crash response roadside assistance and Family Link) and analysis of real time data collected from the vehicles in rapport with research and development , quality control and manufacturing to ensure customer safety and ownership experience. We are
The Individual would be leading the effort to develop “first in line” insights, Key performance indicators and effectiveness of the solutions that are being implemented. The individual is responsible to provide technical expertise to develop analytics driven solutions to help achieve their business goal. The individual will work as a member of a multi-disciplinary and cross organizational team of various experience levels that will be driving solution by designing, developing, and deploying analytic models to measure performance to support critical business areas.

Responsibilities
As a data engineer ,the individual will work with a wide variety of data sources including Oracle, Teradata , Greenplum, Hadoop databases to extract information and integrate to help create “key performance indicators” - The KPI's would serve as a benchmark of the critical program's success . The KPI's would cover the aspects of operational health, effectiveness, and pain points of the digital implementation. Effective gap analysis to understand the failure rates and the cause of the failures is also a key responsibility. The individual would also be responsible for implementation of Text Analytics /ML programs to better our understanding of business analytics , train models to act as better predictors of the conversational intents ( Text parsing and topic modelling) , volumetric trends towards specific lines of business and overall pain point understanding . With multiple initiatives going on, there would be holistic integration in the strategy employed as to achieve a unified picture of all programs.
Gather the data through mining computer data through software, to improve performance and reduce costs. Effectiveness of the solutions through a cost model would also be a critical responsibility that the individual would work with along with a broader team.

Required Technical Skills/Tools
• Expert in using SQL across Oracle, Hadoop/Hive databases, systems.
• Expert in ETL systems – Via Batch SQL, Data Stage (awareness)
• Experience with extraction and loading into Hadoop/Hive
• Business intelligence and data analysis software — IBM Cognos Impromptu; Tableau, Oracle Business Intelligence Enterprise Edition
• Operating system software — Bash, UNIX, Shell script
• Knowledge of IVR (Interactive voice Response systems)
• Knowledge and Expertise in vehicle-based telematics architecture
• Specialized knowledge of vehicle based health programs, High Speed telematics ingestion and backend -vehicle communication
• Data base management system software — Apache Hadoop/HDFS; Oracle PL/SQL; Teradata Database, Apache Cassandra, Apache Hive, NoSQL db
• Advanced proficiency with using text Analytics using Hive.
• Familiarly and experience with implementing machine learning models (Create data sets, train models, explain correlations between dependent and independent variables)
• Familiarity with statistics and ability to explain why a specific model was chosen
• Familiarity with Object or component-oriented development software — Python.
• Presentation software — Microsoft PowerPoint
• Project management software —Microsoft Project; Microsoft SharePoint.
• Development environment software —; Eclipse IDE; Microsoft Visual Studio

Preferred Technical Skills/Tools
• Knowledge of Data lakes, Datawarehouse, Operational data stores as it relates to RDBMS and Big Data Technologies.
• Knowledge of Kafka streaming systems, Microservices architecture
• Call center telephony hardware/software integration to deliver critical Voice based services
• Knowledges of best CX practices for operational performance efficiencies – Determine right KPI's, perform FMEA analysis, determine pain points, provide solutions for corrective actions.
• Understand Natural Language Processing