About Scribble Data
Scribble Data is an MLOps product company, which provides foundational blocks on which enterprises build their ML models and analysis. Our customers trust us with their data, and with Scribble, have managed to significantly reduce friction in the consumption of data. We work smart, invest in tools and tech that are on the cutting edge of data science, and package all that we’ve learnt about efficiency and data mileage into our products.
Our modular feature store, Enrich, comprises a number of pre-built feature engineering apps to help data teams cut time-to-market for each data science use case including unified metrics, customer behavioral modeling, ML model building, and recommendations.
Enrich streamlines the data prep process with versioned pipelines, delivering continuously updated data through intuitive interfaces and surfacing context around datasets via extensive metadata and lineage tracking.
About the role
We are searching for a capable platform engineer to work on our flagship feature store product, Enrich. You will be focused on extending functionality for Enrich with high attention-to-detail ensuring trust, robustness, performance, and ease of use. Here are all the details you’ll need, to see if we can work together:
- You will develop high-performance data processing systems for dealing with internet-scale data.
- You will develop and deploy robust, distributed, scalable, real-time, data processing infrastructure that can support various downstream applications including reporting, analytics, user intelligence, machine learning, and decision support.
- You have strong system-level thinking and problem-solving ability paired with the love to build and ship robust code.
- You have strong software engineering skills and can set up and operate well-thought-through development systems and processes.
- 8+ years of industry experience building data infrastructure including packaging, deploying and monitoring data systems
- Fluency in Python, SQL - Java knowledge will be a plus
- Proficiency in designing, implementing and automating systems for data workflow management
- Proficiency in developing and publishing APIs using web services
- Proficiency in designing robust, scalable data architectures
- Experience using distributed storage (e.g. S3), serverless architecture (e.g. Lambda), streaming data (e.g. Kafka), scalable search (e.g. Elasticsearch)
- Experience with containerization (e.g. Docker/Kubernetes), and other deployment tooling
- Experience with big data technologies like map-reduce, NoSQL, Spark, HBase, Hive
- Experience with data security protocols, data access controls, AWS/GCP/Azure security mechanisms at the data and access levels, database security, scripting attacks, API security
- Having built and shipped a product at a startup will be a plus
- Bachelors/Masters degree in Computer Science
Does this sound like you?
- You like adventure and have a stomach for learning and unlearning every day
- You are excited by powering up a whole generation of upcoming data applications
- You dream big and believe that hard problems need streamlined systems and massive amounts of data to tackle effectively
- You embrace uncertainty and can develop processes and systems to handle rapidly evolving requirements
- You have a sense of humour
GET EXCITED. Because you're about to make a huge impact.
Scribble Data is growing rapidly, and hiring for remote positions across the globe to service its customers across four continents (and counting). We think of this phase of hiring as extending Scribble's core team, so if you want to get in on the ground floor, now would be a good time to look our way.
WHAT WE OFFER
- Work from home or your preferred location
- A work culture that helps you innovate and evolve continuously, and the freedom to work in the hours you feel the most productive
- A chance to shape the future of data and MLOps
- Minimum 8 weeks paid parental leave, irrespective of gender
Work Experience(in years)4 - 10 Years