4+ years of development experience building and maintaining ETL pipelines
3+ years of experience working with database technologies and data development (e.g., Python, PLSQL)
Experience mentoring junior team members through code reviews and best practices
Deep understanding of writing test cases to ensure data quality and reliability
Proven track record of advancing new technologies to improve data quality and reliability
Continuously improve the quality, efficiency, and scalability of data pipelines
Expert skills in working with queries/applications, including performance tuning, utilizing indexes, and materialized views to improve query performance
Identify necessary business rules for extracting data along with functional or technical risks related to data sources (e.g., data latency, frequency)
Develop initial queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and defining a path to deployment
Familiar with best practices for data ingestion and data design
Job Responsibilities:
The Senior Data Engineer will lead the Enterprise Data Services team, transforming data from various systems to provide insights and analytics for business stakeholders. You will leverage cloud-based infrastructure to implement scalable, resilient, and efficient technology solutions.
Collaboration with Data Engineers, Data Analysts, DBAs, cross-functional teams, and business leaders is essential.
You will architect, design, implement, and operate data engineering solutions using Agile methodology to empower users to make informed business decisions.