Data Engineer

Purpose

Reporting to the Senior Manager Data Science & Analytics, the Data Engineer is responsible for documenting data models, architecting distributed systems, creating reliable data pipelines, combining data sources, architecting data stores, and collaborating with the data science teams to build the right solutions for them.

Responsibilities

• Assisting in quality control of quantitative and qualitative research projects.
  
• Designing, building and support data processing pipelines to transform data using Cloud technologies e.g. AWS, Azure, GCP etc.
  
• Working with business analysts to understand business requirements and use cases.
  
• Developing and executing quality assurance and test scripts.
  
• Building survey and voter file data pipelines.
  
• Designing, building data assets in cloud solutions and/or oracle ODI.
  
• Designing and developing tools for internal team use to simplify complex task flows.
  
• Designing schemas, data models and data architecture for cloud environments.
  
• Implementing data flow scripts using Unix and/or scripting.
  
• Creating scripts and workflows to automate repeated data processing tasks.
  
• Working with data team to identify opportunities for task automation and helpful tools.
  

Skills

• Ability to work across regional teams with strong communication and collaboration skills
  
• Tendency to go above and beyond to make things work; manage own and others work to meet the deadline and assist other team members in their deliverables
  
• Ability to identify solutions and make the complex simple.
  
• Ability to breakdown complex problems into simple solutions
  

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Actuarial Science, Information Systems, Economics, Statistics, or a related quantitative field.
  
• Experience and knowledge of coding language such as Python.
  
• Good experience and knowledge of the SQL query language.
  
• Understanding of star schemas and data warehouse concepts.
  
• Knowledge of AWS/Azure tools and technologies
  
• Beneficial - ETL and ELT experience - both batch and microservices-led.
  
• Minimum three (3) years’ experience in a data engineer role or similar.
  
• Experience with data pipeline and workflow management tools: Airflow, etc
  

Purpose

Reporting to the Senior Manager Data Science & Analytics, the Data Engineer is responsible for documenting data models, architecting distributed systems, creating reliable data pipelines, combining data sources, architecting data stores, and collaborating with the data science teams to build the right solutions for them.

Responsibilities

• Assisting in quality control of quantitative and qualitative research projects.
  
• Designing, building and support data processing pipelines to transform data using Cloud technologies e.g. AWS, Azure, GCP etc.
  
• Working with business analysts to understand business requirements and use cases.
  
• Developing and executing quality assurance and test scripts.
  
• Building survey and voter file data pipelines.
  
• Designing, building data assets in cloud solutions and/or oracle ODI.
  
• Designing and developing tools for internal team use to simplify complex task flows.
  
• Designing schemas, data models and data architecture for cloud environments.
  
• Implementing data flow scripts using Unix and/or scripting.
  
• Creating scripts and workflows to automate repeated data processing tasks.
  
• Working with data team to identify opportunities for task automation and helpful tools.
  

Skills

• Ability to work across regional teams with strong communication and collaboration skills
  
• Tendency to go above and beyond to make things work; manage own and others work to meet the deadline and assist other team members in their deliverables
  
• Ability to identify solutions and make the complex simple.
  
• Ability to breakdown complex problems into simple solutions
  

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Actuarial Science, Information Systems, Economics, Statistics, or a related quantitative field.
  
• Experience and knowledge of coding language such as Python.
  
• Good experience and knowledge of the SQL query language.
  
• Understanding of star schemas and data warehouse concepts.
  
• Knowledge of AWS/Azure tools and technologies
  
• Beneficial - ETL and ELT experience - both batch and microservices-led.
  
• Minimum three (3) years’ experience in a data engineer role or similar.
  
• Experience with data pipeline and workflow management tools: Airflow, etc