Summary:
The Data team is responsible for leading efforts to ingest, structure, and model our data to support critical decision making. Our enterprise data warehouse is based on AWS Redshift, supporting Looker analytical dashboards, and is backed by an AWS data lake. In addition to analytics, the data warehouse also supports an active and growing data science practice.

The ideal candidate will have experience building and supporting data platforms that help end users make sound business decisions. This includes data pipeline creation, data quality management, system reliability, job orchestration and recovery aka “Data Ops”. In additional to technical competency, they should be truly motived to empower end users.

Responsibilities

• Implement data pipelines using agile, iterative processes to deliver value quickly
• Treat data quality, reliability, and documentation as fundamental acceptance criteria for data pipelines
• Collaborate with the team to make the best technology choices
• Deliver solutions that ensure data accuracy, high availability, robust security, and that are built for rapid scaling
• Create and maintain data models, data catalogues, and data security.

Qualifications

• 3-5 years experience with data engineering or data warehousing, or an equivalent data-oriented software engineering background
• 2-3 years experience with ETL technologies (e.g. Talend, Informatica, Matillion)
• 2-3 years experience with key AWS technologies (Redshift, S3, IAM; also Kinesis, Lambda, EMR, Spark, Hive)
• 3-5 years of experience with SQL
• Experience in optimizing queries and tuning database performance
• Familiarity with data analysis and data science tools (Looker, Python, Jupyter, R) is a plus
• Python or Java experience is a plus