Responsibilities
:
1. Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our data warehouse.
2. Maintain and build on our data warehouse and analytics environment.
3. Produce scalable, replicable code and engineering solutions that help automate repetitive data management tasks.
4. Identify, design, and implement process improvements such as: improving database performance, optimising data delivery and re-designing infrastructure for greater scalability, and maintainability among many things
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources within our AWS and data warehouse ecosystem.
6. Implement and monitor best in class security measures in our data warehouse and analytics environment, with an eye towards the evolving threat landscape.
7. Work with stakeholders including the Engineering, Product, Data Analytics and Design teams to assist with data-related technical issues and support their data infrastructure needs.
8. Work with data and analytics experts to strive for greater functionality in our data systems.
9. Help data analysts troubleshoot their SQL, Python, or R code.
Skills & Experience:
10. Strong command of relational databases and SQL. Extract, Transform, and Load (ETL) data into a relational database. We use Snowflake, Redshift, DynamoDB, MySQL and DBT.
11. Proficiency with Python or R, especially for data manipulation and analysis, and ability to build, maintain and deploy sequences of automated processes with these tools.
12. Advance data manipulation skills: read in data, process and clean it, transform and recode it, merge different data sets together.
13. Demonstrated ability to write clear code that is well-documented and stored in a version control system. We use Git.
14. Use APIs to push and pull data from various data systems and platforms.
15. Experience in building and maintaining a dimensional data model using type 2 dimensions.
16. Demonstrated ability to learn new techniques and troubleshoot code without support, ex. find answers to common programming challenges on Google. In other words, be able to learn on the job.
17. Excellent listening, interpersonal, communication and problem solving skills.
18. Demonstrated ability to work effectively in teams, in both a lead and support role.
19. Demonstrated ability to work independently and be a self-starter.
Nice to have:
20. Software engineering, data science, data analytics experience
21. Experience in Docker
22. Knowledge of building data lake or data warehouse.
23. Knowledge of handling streaming data.
24. Experience in Infrastructure as Code and CICD practice.
25. ML or predictive analytics experience.
26. Experience in web or mobile application development.
Employee Perks - Share Options - Paternity/Maternity Leave Policies - Flexible Work Policy - Company wide Development & Coaching - Hackathons - Awards - "Your Time to Shine & Celebrate Success"- Social Events & variety of social clubs (Books, LGBT, Games, Sports) - Mental Health Support - Munch & Learns Deputy believes in equal opportunity and that inclusiveness and diversity promotes innovation. Our global team members are from a variety of cultures. And we welcome different perspective and skills. #LI-Hybrid