Data Engineer - Resource Logistics, Inc.

What you ll do:
" Lead technical data solutions, including custom development working with cross project teams in delivering projects.
" Define overall ETL/ELT Clienthitecture including key designs on integration standards such as loading real time/batch data, CDC, data validation, data enrichment etc.
" Clienthitect solutions based on specific project requirements, considering best practices and performance standards while promoting reusability
" Building data model and semantic layer with automated data exception framework
" Ability to manage and participate as a senior Data Analyst gathering and analysis of source data, processing logic, and operational system usage.
" Responsible for the solution design, hands-on development, technical tasks oversight, release management and implementation of data products and features.
" Deep hands-on knowledge of data integration and data pipeline methodologies and API platforms
" Hands-on engineer working with other cross functional teams following agile methodologies.
" Analyze issues, reverse engineer where needed to come up with solutions to resolve issues in a timely manner
" Responsible for maintaining teams commitment to excellence and high standards in a collaborative environment
" Work with team to align solutions and data integration with business strategy and objectives.
" Apply broad in depth business and technical knowledge advance technical direction.

Skill Set Requirements:
" 6+ years in a direct role as a Developer / designer / Clienthitect for ETL, data warehouse and data lake systems.
" 4+ years of solid data warehousing, integration methodology experience.
" 4+ Years - Data modeling experience to deliver both logical model & physical design for transaction and analytical systems.
" Candidate must have strong technical expertise in SQL and Snowflake.
" Must have advanced technical understanding with tools and products used in data warehouse and data integration development, such as Pyhton, Airflow, Glue, DBT, Workato
" Solid hands-on experience in data modeling, data feature engineering.
" Broad exposure in the new techniques in data warehousing and data integration technology
" Experience in data lake Clienthitecture and design
" Strong understanding of data Clienthitecture in a AWS cloud environment
" Able to communicate effectively with all levels of management in a clear and professional manner; verbally and written.
" Strong technical design and documentation skills