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Resp & Qualifications
PURPOSE:The Lead Data Engineer is responsible for orchestrating, deploying, maintaining and scaling cloud OR on-premise infrastructure targeting big data and platform data management (Relational and NoSQL, distributed and converged) with emphasis on reliability, automation and performance. This role will focus on leading the development of solutions and helping transform the company's platforms deliver data-driven, meaningful insights and value to company.ESSENTIAL FUNCTIONS:- Lead the team to design, configure, implement, monitor, and manage all aspects of Data Integration Framework. Defines and develop the Data Integration best practices for the data management environment of optimal performance and reliability.
- Develops and maintains infrastructure systems (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using Hadoop or equivalent MapReduce platform.
- Provides detailed guidance and performs work related to Modeling Data Warehouse solutions in the cloud OR on-premise. Understands Dimensional Modeling, De-normalized Data Structures, OLAP, and Data Warehousing concepts.
- Oversees the delivery of engineering data initiatives and projects. Supports long term data initiatives as well as Ad-Hoc analysis and ELT/ETL activities. Creates data collection frameworks for structured and unstructured data. Applies data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources.
- Enforces the implementation of best practices for data auditing, scalability, reliability and application performance. Develop and apply data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources.
- Interprets data, analyzes results using statistical techniques, and provides ongoing reports. Executes quantitative analyses that translate data into actionable insights. Provides analytical and data-driven decision-making support for key projects. Designs, manages, and conducts quality control procedures for data sets using data from multiple systems.
- Improves data delivery engineering job knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; benchmarking state-of-the-art practices; participating in professional societies.
- Knowledge and understanding of at least one programming language (i.e., SQL, NoSQL, Python).
- Knowledge and understanding of database design and implementation concepts.
- Knowledge and understanding of data exchange formats.
- Knowledge and understanding of data movement concepts.
- Strong technical and analytical and problem solving skills to troubleshoot to solve a variety of problems.
- Requires strong organizational and communication skills, written and verbal, with the ability to handle multiple priorities.
- Able to effectively provide direction to and lead technical teams.
- Must be able to meet established deadlines and handle multiple customer service demands from internal and external customers, within set expectations for service excellence. Must be able to effectively communicate and provide positive customer service to every internal and external customer, including customers who may be demanding or otherwise challenging.