Role
Data Engineer – AWS
Summary
The Data Engineer’s primary responsibility is to define data models and data sources for analytics platforms, gather data from the business, and clean the inputs in order to provide ready-to-work inputs for Data Scientists. They are responsible for connecting and modelling complex distributed data sets to build repositories and managing data related contexts ranging across small to large data sets.
Primary Responsibilities
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional and 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 Cloud big data technologies
- Build analytics tools that utilize the data pipeline to provide actionable insights into Client 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
Domain Expertise
- Bachelor’s degree in Computer Science or equivalent; Masters preferred
- 3 years’ hands-on experience with a strong data background
- Extensive experience working with big data tools and building data solutions for advanced analytics
- Practical knowledge across data extraction and transformation tools (e.g., Informatica, Alteryx, other modern tools)
- Knowledge in data architecture, defining data retention policies, monitoring performance and advising any necessary infrastructure changes
- Solid development skills in AWS Platform: AWS DMS, Glue, Redshift, S3 and Athena SQL
- Hands-on mastery in big database systems, including distributed file systems, traditional RDBMS, NoSQL, Cloud technologies, and in-memory database systems.
- Comfortable in dashboard development (e.g., Tableau, Powerbi, Qlik, etc) and in developing data analytics models (R, Python, Spark)
Individual Skills
- Strong communication skills, especially in articulating technical concepts
- Utilizes team collaboration to create innovative solutions efficiently
Agile Experience
- Strong understanding of Agile methodologies
Mindset & Behaviours
- Intellectual curiosity and desire to take ownership over projects
- Contributes to internal and open-source technical knowledge
Number of Vacancies
1