MINDBODY’s Data Science department makes sense of our data world through meaningful and actionable insights, identifying trends, delivering reports, informing product and infrastructure advancements, and promoting a culture of data-driven decision making.
The Data Engineering (DE) branch of MINDBODY’s Data Science department is focused on providing innovative and large-scale data platform solutions in a shared services model to support enterprise data needs of MindBody. This involves building data pipelines to pull together information from different source systems; integrating, consolidating and cleansing data; and structuring it for use in reporting and analytical applications. This team also architects distributed systems, data stores, and collaborates with data science teams in building the right solutions for them. The data provided by the DE team is used by data science team in supporting key functions and initiatives within Product Development, Business Development, Customer Experience/Success, Marketing and Sales at MindBody.
Data Warehouse Engineer I focuses on integrating, consolidating, and cleansing data from multiple source systems including the data from companies acquired by MindBody. This position works closely with their manager to prioritize tasks that are important in supporting our product and business units.
MINIMUM QUALIFICATIONS AND REQUIREMENTS:
- Bachelor’s degree or equivalent experience
- 1-year (preferably 2-3 years) experience building/operating systems for data extraction, ingestion, and processing of large data sets
- Basic proficiency in MS SQL, SSIS (or any other ETL tool), R, Python, Amazon RedShift, MS Azure
- Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist, Business Analyst
- Hands-on experience with SQL query language, data warehouse, RDBMS and common BI tools and techniques
- Strong attention to detail, analytical mindset, and highly organized
- A desire to work in a fast-paced, potentially ambiguous, start-up-like atmosphere
- Strong technical aptitude and demonstrated ability to quickly evaluate and learn new technologies
- Strong interpersonal skills, with the ability to work independently and within a team environment
PRINCIPAL DUTIES AND RESPONSIBILITIES:
- Develop new ETL processes to fulfill the data needs of data science and other departments
- Utilize expertise in data modeling, ETL architecture, and report design for department initiatives
- Produce detailed documentation including data flow diagrams, logical diagrams, and physical diagrams as needed
- Ensure the data collection pipeline and data analysis infrastructure meet the needs of the business
- Acquire strong knowledge of data structures, analysis, replication and distributed/ relational data & database mapping
- Provide insights and analyses around product and customer data
- Assist with SQL code review process for purposes of learning, asking new questions and finding errors
- Assist with development of new scripts, KPIs and dashboards
- Consult with management to understand current and future business goals and strategies, and ensure that high-visibility reporting and analysis is aligned
- All other duties as assigned