Hybrid Lead Engineer- Big Data na JCPenney

Lead Engineer- Big Data
The Lead Engineer – Analytics (Advanced Software Engineer) will report to a Senior Manager - Analytics.  Using Big Data technology, you will be responsible for designing, developing, implementing and supporting data analytics solutions utilizing cloud architecture. 
Primary Responsibilities:
•    Lead, build and deliver projects with high impact and cross-portfolio scope, complexity and collaboration with cross-functional teams, both business and technology
•    Identify technical implementation options and issues
•    Play a key role in defining the future Technology architecture and develop roadmaps of the systems, platforms and/or processes for the company across disciplines
•    Provide technical leadership and coaching to other engineers and architects across the organization
•    Act as expert and point of contact in cross-scrum business/technology/domain area
•    Partner and communicate cross-functionally across the enterprise
•    Provide the highest level of expertise for the specification, development, implementation and support of Analytical solutions (e.g. Datameer, Hive, Python, Redshift, Tableau)
•    Explain technical solutions and issues to senior leaders in the company in non-technical, understandable terms
•    Interact with business teams to gather, interpret and understand their business needs and create design specifications
•    Foster the continuous evolution of best practices within the development team to ensure data quality, standardization and consistency
•    Continuously seek Data Lake platform and data ingestion improvement opportunities that ensure optimal use of the environment and improve stability.  Lead efforts to implement the solutions. 
Core Competencies & Accomplishments:
•    10+ years of professional experience
•    4+ years of experience with Big Data technology and analytics
•    JCPenney business domain knowledge preferred
•    Proficient in query languages such as SQL, Hive
•    Proficient in using Big Data tools (e.g., Hadoop, NoSQL DB, Hbase) and API development and consumption
•    Proficient in data preparation and manipulation using Datameer tool
•    Experience with one or more languages (e.g., Python, Java)
•    Experience with SOA, IaaS, and Cloud Computing technologies, particularly in the AWS environment
•    Experience with Hadoop/Hive, Sqoop and Spark
•    Experience with ETL and ELT data modeling
•    Experience with data visualization tools like Tableau
•    Experience with continuous software integration, test and deployment
•    Experience with agile software development paradigm (e.g., Scrum, Kanban)
•    Ability to work within a dynamic environment with evolving requirements and capability goals
•    Self-motivated.  Capable of working with little or no supervision.
•    Maintains up-to-date knowledge in the appropriate technical areas
•    Strong written and verbal communication.  Able to present and hold meetings with key business and technology partners, enterprise architects and vendors.