About The Position
Fireblocks Data engineers will build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret.
The ideal candidate must be technical enough and up to date with modern technology to automate manual data collection processes. In addition the ideal candidate should be experienced in implementing ML/AI to automate manual data quality operations.
What You'll Be Doing:
- Be a very skilled architect with cross-functional and cross-domain know-how.
- Sketch the data solution architecture, then implement, optimize, monitor and govern the implementation.
- Design & maintain our team’s data pipelines and manage our internal database
- Partner with business, product, engineering and data science teams to unlock the power of leveraging data across Fireblocks by translating business requirements/problems to solutions, products, or services.
- Partner with development teams in the data design of complex solutions and ensure that they are in alignment with the data architecture principles, standards, strategies, and target states.
- Enforcing data architecture standards, procedures and policies to ensure consistency across different program and project implementations.
- Adopting industry leading technologies to support best-in-class business capabilities for high performance computing and data storage solutions
- 5+ years of hands-on experience with one or more major programming/scripting languages such as Java, Linux, Python, NodeJS and/or R
- 4+ years of experience in working with ETL tools such as Informatica, Talend, Pentaho and/or similar tools.
- 4+ years of experience in designing solutions for multiple large data warehouses with a good understanding of cluster and parallel architecture as well as high-scale or distributed RDBMS and/or knowledge on NoSQL platforms (e.g. PostgreSQL, Redshift, BigQuery, Snowflake, DynamoDB, Neo4J, MongoDB, Cassandra, HBase, etc.).
- Current hands-on experience with industry leading data management tools that support the data lifecycle, and capable of setting and driving long term data architecture roadmaps in alignment with corporate strategic objectives.
- Experience in message queuing, stream processing, and highly scalable ‘big data’ tools and technologies is a plus
- Experience and knowledge with data security and privacy concerns
- Strong analytical skills and algorithmic problem-solving skills.
- Knowledge of / experience with Machine Learning is a plus