Analytics Engineer at Balena
You will build scalable analytics architecture and frameworks, and dig deep into the data to identify patterns and trends.
- Background in Data Science, BI, Mathematics, Engineering or a related field
- Strong analytical skills with a passion for data quality
- Knowledge of best practices and common tools for data processing and analysis
- Product intuition – learning about our customers, articulating use cases, understanding their needs and challenges, and developing scalable solutions
- Ability to manage ambiguity, make critical trade-off decisions, and push projects to completion
- Continuous improvement mindset, and desire to make self and others more effective
- Excellent verbal and written communication skills, and fluency in English
- Firm grasp of technologies like Typescript, Node.js, Bash, Go, and Docker
- Familiarity with technologies like PostgreSQL, Typescript, and React
- Experience developing business intelligence and data processing tools
- Working knowledge of growth, product optimization, and experimentation practices
- Experience working with analytics and marketing performance platforms (we use Amplitude)
- Background in partnering with product and software engineering teams
What you will work on
At balena, we aim to continually improve user experience by removing friction and maximizing adoption, engagement, and retention. As an Analytics Engineer, you will develop a deep understanding of our platform and analytics architecture and work closely with engineers to build and enhance the infrastructure for processing various data streams and delivering clear and accurate analysis. You will be equal parts analyst, developer, and product owner.
You will build scalable analytics architecture and frameworks, and dig deep into the data to identify patterns and trends. Most importantly, you will help develop our self-service analytics capability – building tools and processes that enable our team, and eventually, our users, to explore, uncover insights about user engagement, and make strategic decisions.
- Continuously evolve our data products and components to scale and automate data collection, analysis, monitoring, and experimentation across the platform
- Explore user paths, analyze activity and feedback, provide insights, and craft visualizations to facilitate product and user behavior understanding
- Define and track success metrics and design dashboards to provide visibility into product performance, user flows, funnel conversion, and feature adoption
- Build an experimentation framework and develop hypotheses to determine the impact of potential improvements throughout the product development lifecycle
- Partner with engineers to implement tools and user interfaces that will allow our team to run experiments, gather data, and perform analysis
Make sure to let us know if any of these items apply to you!