Job Description :
Notes:

These resources will be working on the Executive Reporting platform DOMO - a Cloud based data/analytics platform, targeted for executive metrics.  These are Principal level positions and are expected to get up and running quickly. 6 month contract with option to extend. Can be based in either MMK or NC, with a preference for MMK. Key skills are Cloud Data Engineering, AWS, Snowflake, Kafka, DOMO (preferred), EMR (elastic map reduce), must be hands on Data Engineers, tech lead level, fine detail and building of systems, hands on coding.

The Expertise We’re Looking For


This role requires 12+ years of experience in multiple IT areas that include data architecture, data modeling, BI tools, design, integration, evaluation, and development
Demonstrated data architecture, data modeling and solution design experience
Bachelors or Master’s Degree in a technology related field (e.g. Engineering, Computer Software) required




The Purpose of the Role

The Principal Data Engineer will be accountable for developing both enterprise and business unit specific data integrations and analytic platforms. Additionally, the person will be responsible for collaborating with key partners (e.g. business unit technology teams, Data architecture, analytics designers) in the implementation of data pipelines, data stores etc.


Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
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 with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our 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 our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.




The Skills required


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.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
A successful history of manipulating, processing and extracting value from large disconnected datasets.
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.
We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

Experience with big data tools: Hadoop, Spark, Kafka, etc.
Experience with Snowflake Analytics Warehouse
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience with AWS cloud services: EC2, EMR, RDS, Redshift
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
             

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