Position: Middle Senior Data Engineer (Scala)
Company: AgileEngine
Experience required: 2y
English level: upper

There is value in data waiting to be unlocked. Pattern brings cutting edge AI and natural language processing to personal injury cases so that you can improve accuracy, minimize costs, and move faster.

**With us you can**
Work in a dream team of A-players, 65% of whom are seniors
Create solutions that will be used by global giants like Paramount, IBM, Deloitte, Volkswagen, and others
Enjoy flexibility by operating remotely or onsite in one of our R&D centers
Shape your success journey through a personalized growth roadmap tailored to your interests and goals
Embrace agility — forget about micromanagement and old-school hierarchies

**What you will do:**
Own the full software development lifecycle for user-facing features
Constantly pay down technical debt and improve software development processes through tool development
Constantly learn the latest trends and tools applicable to PatternData problem, evaluating and integrating them as appropriate
Work with management to define and refine backend service technology roadmap
Evangelize and educate best practices for maintainable high-concurrency server code among the rest of the software organization

**Our team is missing someone who has**
Fluency and at least +3 years of experience in Scala;
Proven passion for everything you build to be elegant and maintainable, in architecture and implementation
Intuition for and experience in design of highly fault-tolerant architecture of loosely-coupled services
Strong individual contributor, self-motivated, and a proven team player
Demonstrated eagerness to learn and develop new experience
**Upper-intermediate English**

**What will be a plus?**
Knowledge of JavaScript, React and any other frameworks
Experience supporting a distributed production backend with high uptime metrics

**Expertise with some of the following technologies:**
– Container-based virtualization (Docker)
– Distributed pub/sub frameworks (Kafka), distributed high-throughput key-value storage (Redis)
– Big data storage (Cassandra, Redshift, BigQuery) and processing (Cloud Dataflow, Spark)
– High-concurrency relational databases (PostgreSQL)
– Distributed log collection and analysis
Advanced academic training in distributed systems, security, or a related field