Senior ETL Data Engineer

What you’ll do:

• Lead technical data solutions, including custom development working with cross project teams in delivering projects. 
• Define overall ETL/ELT architecture including key designs on integration standards such as loading real time/batch data, CDC, data validation, data enrichment etc.
• Architect 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 / architect 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 architecture and design
• Strong understanding of data architecture 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