Data Engineer

À propos de l’offre d’emploi

Laevitas is a data analytics platform based on quantitative finance models for the crypto-asset market. We are looking for a Data Engineer to join the team and be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection. The ideal candidate is an experienced data pipeline builder who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our data analytics platform roadmap.

Responsibilities

Create and maintain optimal data pipeline architecture
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work and coordinate with different teams to assist with data-related technical issues and support their data infrastructure needs.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our platform.

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Required Qualifications

We are looking for a candidate with 3+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
Experience with object-oriented/object function scripting languages: Python
Experience with big data tools: Spark, Kafka
Experience with relational SQL and NoSQL databases, including Postgres and MongoDB
Experience with AWS cloud services: Lambda, EC2, EMR, RDS
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Strong project management and organizational skills.
Experience supporting and working with cross-functional teams in a dynamic environment.

Preferred Qualifications

Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
A successful history of manipulating, processing and extracting value from large disconnected datasets.
Strong analytic skills related to working with unstructured datasets.

We offer