* Team8 Portfolio Company
Harmonya helps retailers and manufacturers overcome the limitations caused by legacy data structures and unlock the true value of their data.
Harmonya is an AI-powered product data classification and enrichment platform for retailers and manufacturers. Leveraging proprietary ML and AI models, Harmonya synthesizes data from trillions of alternative data points to generate a holistic and dynamic view of products sold across the country.
Team8 is a company-building venture group that builds and invests in companies specializing in Data, AI, Fintech, and Cybersecurity. The Team8 model supports entrepreneurs with an in-house team of researchers, growth experts, and talent acquisition specialists, and a “village” community of enterprise c-level executives and thought leaders. Whether building a new company from scratch or investing in companies already on their journey, Team8 brings a rich ecosystem to work hand in hand with entrepreneurs in accelerating.
We’re looking for brilliant data engineers to join our rapidly growing team.
You will join a team consisting of senior software and data engineers that drive our data platform from data acquisition, to processing and enrichment and all the way to business insights. You will join an early stage team and company and will have a major impact on the decisions and architecture of our various products.
- Build data acquisition pipelines that acquire, clean, and structure large datasets to form the basis of our data platform and IP
- Build data processing pipelines integrating many different data sources and forms
- Leverage relational and nosql databases to our product needs
- Develop and maintain features in production to serve our customers
- Collaborate with product managers, data scientists, data analysts and full stack engineers to deliver our product to top tier retail customers
- Participate in designing and developing our data platform architecture
- At least 3 years of experience with data engineering in Python (or equivalent language)
- Experience with cloud platforms (AWS, Google GCP, Azure), working on production grade products at large scale and complexity. Experience in working with Docker/Kubernetes is a big advantage.
- Hands-on experience with data pipeline building specifically on cloud infrastructure
- Hands-on experience with analyzing new datasets
- Advantage: Hands-on experience with relevant tools (Jupyter notebooks, Anaconda etc)
- Advantage: Hands-on experience with data science tools, packages, and frameworks
- Advantage: Hands-on experience with ETL Flows