We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our developers, analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
Our purpose and our reach, your opportunity. Top Hat is the leading teaching platform that professors use to create an active learning environment. Using Top Hat, professors can transform students' smartphones and laptops into tools of engagement, leading to increased attendance, higher grades, and a more effective lecture experience. We aim to be the premier way for professors to interact with students both in and out of the classroom.
As a key member of our growing data team you will:Create and maintain optimal data pipeline architecture.Assemble large, complex data sets that meet functional and non-functional business requirements.Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, AWS, and Google ‘big data’ technologies.Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.Work with stakeholders including the Engineering, Product, and Operations teams to assist with data-related technical issues and support their data infrastructure needs.Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.Work with data and analytics experts to strive for greater functionality in our data systems.
Some of the reasons we attract great people:The data team is rapidly scaling up, where there are opportunities to build new processes and tools.The impact you will make extends beyond just the success of the company but the prosperity of the education environment.We have a very good business and strong revenue growth. You will be exposed to a business past start-up mode and scaling quickly.We’re just the right size for individuals that want stability but don’t want to be a number.We offer meaningful development and leadership opportunities, backed up with numerous learning opportunities and development plans. Whether it’s leading people or projects, our growth translates into new challenges for those that are motivated.
What you will bring to Top Hat:We are looking for a candidate with 5+ years of experience in a Data Engineer role, and who has attained a degree in Computer Science, Computer Engineering, or a related quantitative field.Experience with a variety of relational SQL and NoSQL databases, such as Postgres, Redshift, and DynamoDB, and advanced working SQL knowledge.Experience building and optimizing ‘big data’ data pipelines, architectures and data sets using data pipelines and workflow management tools such as Airflow or Luigi, stream-processing systems such as Kinesis, or Spark-Streaming, and highly scalable ‘big data’ data stores and tools such as Spark or Kafka.Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.Strong analytic skills related to working with unstructured datasets.Build processes supporting data transformation, data structures, metadata, dependency and workload management.A successful history of manipulating, processing and extracting value from large disconnected datasets.Experience with common AWS and/or Google cloud servicesExperience with object-oriented/object function scripting languages such as Python, Scala, etc.Strong project management and organizational skills.Experience supporting and working with cross-functional teams in a dynamic environment.