Data Engineer

Job Description:

● 2-5 years of experience with Data Warehousing and Big Data technologies.

● Over 2-5 years of experience in designing scalable and secure pipelines for data needs.

● Strong analytic skills related to working with unstructured datasets.

● Strong project management and organizational skills.

● Good experience in NiFi, API and Redshift is a must.

● Experience with AWS cloud services: EC2, EMR, RDS, Redshift is a must.

● Experience in a development language Scala/Python or similar is preferred.

● Good Experience in Spark/Storm/Scala.

● Experience in Amazon Kinesis or a similar tech stack would be a plus.

● High Expertise in Database Modelling (relational, multi-dimensional) & optimization and deep understanding of data architectures.

● Experience with HDFS (Hadoop and Hive) and Relational Database (Teradata, SQL Server, etc.) environments required.

● Skills in Machine Learning, Predictive Analytics, R and Statistical Analysis is preferred.

Responsibilities:

● Create and maintain optimal data pipeline architecture.

● Assemble large, complex data sets that meet functional / non-functional business requirements.

● 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.

● Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

● Keep data separated and secure across national boundaries through multiple data centers and AWS regions.

● Create data tools for analytics and data scientist team members that assist them in building and optimizing products into an innovative industry leader.

● Work with data and analytics experts to strive for greater functionality in data systems.