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 a team to align solutions and data integration with business strategy and objectives.
Apply broad in depth business and technical knowledge to 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.
Candidates 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 Python, 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.