Build, maintain, and implement ELT/ETL pipelines and database structures
Collaborate with other developers on the team
Work with internal technology teams to understand and aid in the implementation of database and data transformation requirements
Design and build data structures throughout all stages of the data lifecycle (raw, refined, analytics/report ready)
Maintain and optimize existing data structures throughout all stages of the data lifecycle (raw, refined, analytics/report ready)
Build ELT/ETL Python scripts to source data from various systems
Validate data and transformations throughout the entire data lifecycle
Analyze data discrepancies to determine root cause and identify correct course of action
Integrate up-and-coming data management and software engineering technologies into existing data structures
Document data lineage, data transformations, business logic, calculations, data dictionary
Provide guidance on automated data QA checks throughout data lifecycle
Ensure that all systems meet the business/company requirements as well as industry practices
Collaborate with members of your team on project deliverables goals
Install/update disaster recovery procedures
Recommend different ways to constantly improve data reliability and quality
Train and mentor others on the team on best practices, techniques, and languages

6+ years of Python programming experience using python packages such as numpy, pandas etc
Strong experience using Python on event-drive programming
Familiar with using python lists, classes, dictionaries to build module/functions etc
Experience analyzing, mapping, and connecting with various source system data
Solid experience with building and maintaining ETL/ELT pipelines using Python
Strong experience with Postgres and PSQL writing data transformation and data structures
Excellent communication skills with the ability to collaborate with non-technical partners
Experience working in an Agile environment working on a Scrum team
Strong understanding of concepts or experience with ETL and ELT, Data pipelines, Data Warehousing and Data Marts, Kimball Vs. Inmon architecture patterns, TDD, Source control, CI/CD, DevOps

Lead Engineer, Data

Key skills