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Bolt engineering teams are working on unique product challenges: complex algorithms for demand prediction, optimal real-time pricing, routing, fraud detection, distributed systems and much more. Volumes are growing at a rapid pace. We are looking for an experienced engineer who is well-versed in data technologies.

Your daily adventures will include

Designing, building and optimising Bolt's Data Platform's infrastructure for scheduling and running Data Pipelines. The main areas include the development of orchestration (Airflow-based), processing (Spark, on Databricks) layers and providing Presto capabilities. You will also work closely with teams responsible for Storage and Analytical Systems (Data Lake, Data Warehouse, Data Modelling) and infrastructure for Data Pipelines and Machine Learning models
Investigating and prototyping new services to improve different aspects of our Data Platform: data governance, data quality, monitoring, alerting, performance, and cost efficiency
Coding mostly in Python, Scala, Java and occasionally TypeScript (previous experience is not required)
Governing data infrastructure in Terraform
Governing and optimizing SQL queries and data storage formats.
Proactively solving technical challenges and fixing bugs
Contributing ideas to our product development roadmap
At Bolt, we are using a modern data stack with Data Mesh architecture with Kafka, S3, Presto, Spark, dbt, Databricks, Airflow, Looker, Fivetran and other relevant solutions to serve thousands of internal customers and millions of external customers.
We are looking for language-agnostic generalists that are able to pick up new tools to solve the problems they face. Check out our blog to know more about all the exciting projects that we are working on:

We are looking for

Experience in at least one of the modern OO languages (Python, Scala, Java, JavaScript, C++, etc)
7+ years of experience in software development
Excellent English and communication skills
Experience with micro-service and distributed systems
Solid understanding of algorithms and data structures
Familiarity with streaming data technologies for low-latency data processing (Apache Spark/Flink, Apache Kafka, RabbitMQ, Hadoop ecosystem)
Experience with Terraform, Kubernetes and Docker
Good knowledge of SQL and experience in at least one of the popular online analytical processing (OLAP) technologies (AWS Redshift, ClickHouse, Presto, Snowflake, Google BigQuery, Databricks, etc.)
A university degree in a technical subject (Computer science, Mathematics or similar)

You will get extra credits for

Experience in building and designing real-time and asynchronous systems
Understanding of NoSQL databases (Redis, ElasticSearch, Apache Cassandra)
Experience in building systems based on cloud service providers (AWS, Azure, Google Cloud)
Experience with Presto and open source committer