Senior Data Engineer
Are you the next Senior Data Engineer at Theory+Practice?
Do you want to leverage data and analytics to solve real-world problems? Have an insatiable appetite for learning and finding solutions? Love to access some of the world’s largest data-sets? Then, you may be the right fit. Theory+Practice is a rapidly growing data science company focused on bringing novel AI/ML solutions to create lasting and actionable value for companies with large data sets.
Our Fortune 500 clients leverage our Intelligent Intervention Framework to find net new signals that highlight the right times and actions to improve customer journeys and maximize key business metrics.
With an ever-increasing client base, we are looking to hire a Senior Data Engineer into our team. The ideal candidate will be passionate about solving high-impact problems for our clients in a fast paced, intellectually diverse team and has experience using data to find opportunities for businesses.
We attract creative, independent thinkers who share a desire for excellence within an open culture. If you have passion for leveraging state of the art analytics to solve complex problems, we invite you to join our team!
A Senior Data Engineer will join a growing group of AI specialists and software engineers at Theory+Practice working closely with client business specialists to systematize data driven insights and decision making. If you have a passion for leveraging new technologies to find simple solutions for complex problems we invite you to consider joining our team!
- Build pragmatic, scalable and rigorous data profiling solutions for TAP customers.
- Build and support data pipelines that enable the creation of net new signals within the client’s environment
- Build and maintain best practices to support the Continuous Integration and deployment of data engineering solutions
- Work collaboratively with TAP colleagues and clients to define problem statements, collect data and define solution approaches
- Build and maintain data models that power TAP analytics and models.
- Leverage Python, Hadoop, Spark and similar Big Data frameworks to deliver efficient analytics
- Communicate clearly the methods, impact and processes you have taken with clients and other stakeholders
- Propose creative analytics use case based on understanding of client’s data and technical feasibility constraints
- 5 to 7 years of industry experience creating and maintaining data pipelines.
- Proven experience performing data extraction, data cleaning, data profiling, outlier detection, exploratory data analysis and sharing results over very large datasets within production environments.
- Very strong SQL skills
- Excellent analytical skills to self-assess and highlight data quality aspects based on both quantitative checks as well as business expertise.
- Good verbal and written communication skills to explain and document insights and methods
- Experience with Python programming.
- Curiosity for understanding business processes and needs in order to inform technical designs is a must.
- High attention to detail is required in order to support drill-downs of large datasets
- Enjoys creating best-in-class solutions within a collaborative team
- Able to break down technical requirements into smaller components and can explain the different approaches to address them as well as the pros and cons of each.
- Advanced degree in a STEM field (e.g. Computer Science, Engineering, Physics, Mathematics, Statistics, Economics, or related field).
- Experience with Big Data systems and frameworks (Hadoop, AWS, GCP, Spark, etc)
- Previous work on Snowflake is a plus
- Experience with Luigi, Airflow, Prefect, etc is also a plus
- Previous experience with cloud computing platforms (GCP, Azure or AWS)