Senior Edge Data Engineer

The Senior Edge Data Engineer will be responsible for edge data collection and manipulation projects involving large volumes of time-series data from various historians/sensors to AWS, design and implement information extraction and processing services in Python. The Senior Edge Data Engineer will be responsible for implementing data integration services related to the enterprise data lake-house, data hub and will also be responsible for building data services related visualization layers. This role involves developing data integration programs based on AWS Services (Glue, Python, Step Functions, Snowflake, HVR, Fivetran, Talend, etc.) This role requires a deep technical understanding of AWS Glue, Snowflake, and Data Engineering technologies including data modeling, optimization, data extraction, loading, transformation, and reporting. This role will manage resolution of complex issues and participate in the design and implementation of new technical solutions and tools.Key Responsibilities:

• Collaborate with stakeholders, technical teams, and cross-functional project teams to implement data analytics solutions based on AWS services, Snowflake, HVR and Analytics tools.
• Lead large-scale data warehousing and analytics projects.
• Develop innovative solutions to complex business and technology problems.
• Design, build and implement automation solutions for application builds, testing and deployment for cloud services.
• Define and implement AWS and Snowflake best practices.
• Identify and resolve data, technical issues and mediate business implications with efficiency, effectiveness and with consistently high quality.
• Collaborate with other team members in the design, implementation, and documentation of solutions for new projects.
• Collaborate with colleagues in Global Data Management team in the design, implementation, and documentation of solutions for daily issues/support, release management, and new projects.
• Collaborate with colleagues in Global Data Management and Cloud teams to improve and optimize global infrastructure for Data Analytics applications and to provide high performance and scalable solutions to meet needs of the Global Users.
• Collaborate with Infrastructure and Cloud teams to define and implement backup, disaster recovery and archival strategy.
• Collaborate with Global Data Management, Infrastructure and Cloud teams to proactively evaluate the capacity and resource utilization of various Data Analytics services, storage, and security.

• 7+ years of hands-on design and development experience implementing Data Warehouses.
• 5+ years of hands-on design and development experience in implementing Data Analytics applications using AWS Services such as S3, Glue, AWS Step Functions, Kinesis, Lambda, Lake Formation, Athena, Elastic Container Service/Elastic Kubernetes Service, Elastic Search, and Amazon EMR or Redshift or Snowflake.
• 3+ years of experience with AWS services such as AWS IoT Greengrass, AWS IoT SiteWise, AWS IoT Core, AWS IoT Events.
• 2+ years of experience with ETL tools like Talend, Alteryx, HVR/Fivetran.
• Expertise in Time Series Databases, SQL and NoSQL databases, data warehouses, and data processing.
• Understanding of emerging time-series, streaming and search technologies.