Data Engineer

At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges. Our work is about more than just AI—it’s about building the future through collaboration and innovation. We believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.

Join the Mission at TeamStation AI!

Where do we come from? We are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.

Role:

The company is looking for an outstanding Data Engineer who would be responsible for building and deploying its data pipelines, data streams, and ETL processes, and managing Data Governance and Data Cleansing, as well as supporting production issues and customer requests. Core skills include Python, SQL, Redshift, and experience with Amazon Web Services.

Responsibilities:

• The data engineer's job responsibilities include (but are not limited to):
• Developing new extract-transform-load (ETL) processes and pipelines. Must be able to manage large volumes of data flowing in from a variety of formats and into a variety of location. You know, standard ETL stuff.
• Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
• That bit above about automating manual processes - that's huge. Automate everything.
• Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
• Working with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues
• Contribute as a team member to testing, QA, and documentation of data pipelines and systems
• Maintaining and developing batch processes
• Optimizing the run-time performance of Python analytics applications
• Building internal software tools to assist processes and information flow for teams across the company.
• Optimize database performance through SQL tuning, index optimization, or architectural changes.

Requirements:

• 3-5 years of experience building ETL pipelines in Python
• Experience building and deploying infrastructure in AWS
• Experience in, or at least a solid understanding of, working in a fast-paced start-up environment
• Strong SQL skills
• Strong Redshift Skills
• Experience working with BI/visualizations tools (e.g., Periscope, Sisense, etc) a plus
• Experience working with AWS Sagemaker tools is a plus
• Experience working in a FinTech company is a plus
• Fluent in relational based systems and writing complex SQL.
• Strong analytical and problem-solving skills with ability to represent complex algorithms in software.
• Strong understanding of database technologies and management systems.
• Strong understanding of data structures and algorithms
• Database architecture testing methodology, including execution of test plans, debugging, and testing scripts and tools.
• Have experience in building real-time streaming data pipelines
• Experience in pub/sub streaming technologies like Kafka, Kinesis, Spark Streaming etc.