Responsibilities:
Anticipate, identify and solve issues concerning data management to improve data quality
Design Data warehouse requirements based on Business Matrix with a proper naming convention prior to Development
Design end to end ETL as per-use cases and business requirements
Implement complex automated workflows and routines using workflow scheduling tools
Drive collaborative reviews of design, code, and datasets implementation performed by other data engineers in support of maintaining data engineering standards
Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues
Explore and learn new best practices/technologies that can improve

Requirements:
Minimum 1 year hands-on experience deploying production quality code
Experience using Python for data processing will be preferred.
Demonstrably understanding of SQL, Data Modeling and Data Warehousing (Redshift or BigQuery)
Hands-on experience implementing ETL (or ELT) and data pipeline tools
Experience with workflow scheduling tools like Airflow
Understanding Linux and docker is a plus
Passionately in love with programming
Excellent team player
Have passion, interest, and willingness to learn and share