Qualifications
●Experience in big data, SaaS/PaaS/IaaS technologies, web development, DevOps infrastructure, enterprise networking, or virtualization/migration/configuration management.
●Experience working with Enterprise Clients, supporting complex technical challenges, identifying knowledge gaps and solutions to up-skill technical knowledge.
●Experience in developing Infrastructure As Code.
Technical Skills / Experience
●Fluent in a number of programming / scripting languages, namely:
○Python
○Javascript (NodeJS)
○SQL
○Shell scripting
●Deep understanding of event driven programming techniques (both locally & in distributed systems)
●Deep understanding of APIs - both creating & consuming
●Understanding of various data filetypes:
○JSON (& ND-JSON)
○CSV
○Avro
●Deep understanding of data structures & data manipulation
●Deep understanding of cloud technologies
●Understanding of & experience with repeatable infrastructure (ie: infrastructure as code: Ansible, Puppet, Terraform, etc)
●Comfortable with Linux / Bash / Shell
●Understanding of containerisation (eg: Docker, Kubernetes, Docker-compose, etc)
●Understanding of distributed serverless technologies (eg: GAE, Cloud Functions, AWS Lambda, Google Data Flow, etc)
●Understanding of data warehousing
○Scalable database storage systems & their use cases
○ETL
○ELT
●Understanding of the use cases & benefits / disbenefits of various database technologies:
○Relational DBs (eg: MySQL, PostgreSQL, MSSQL, etc)
○NoSQL DBs (eg: MongoDB, Elasticsearch)
○Document data stores (eg: Elasticsearch, DynamoDB, Cloud Data Store, etc)
○Bonus Points: Graph DBs (eg: Neo4J, OrientDB, MongoDB)
●Understanding of data preparation & transformation of data for various use cases including data science & marketing activation
●Experience with SaaS solutions, i.e., productivity/collaboration suites and distributed/scale out architectures on IaaS and PaaS on public cloud.
Nice to have Technical Experience
●Exposure to Google Cloud Platform
●Good understanding of marketing systems & workloads
○Martech stacks
○Data processing for martech
●High-level Understanding of Machine Learning basics:
○Feature Engineering
○Training & Evaluation
●High-level understanding of statistics & data preparation for data analysis
●Understanding of orchestration systems such as Apache Airflow / Cloud Composer
●Bonus point: Google Cloud Certified Data Engineer or Google Cloud Certified Cloud Architect Certification (if you don’t have this, we will help you get it as soon as possible after you start)
What WE offer
●A pathway to development of your data engineering skills
●Working on new developments in data science and machine learning.
●Working with enterprise, corporate and government clients
●Start up vibe with the backing of years of industry experience.
●Flexible work hours - everyone has stuff on outside of work, serve your clients (internal & external), get stuff done and come and go as you please outside of that!
Behavioural Competencies
●Highly motivated and delivery focused
●Demonstrated ability to interact positively and constructively with internal stakeholders and partners.
●Ability to successfully manage multiple streams of work in a high-pressure environment.
●Agile mindset with a focus on value driven iterative solutions.
●Ability to communicate with stakeholders and team members.
●Strong sense of ownership and accountability.
●Team player and thrives in a high pace environment.
***Benefits:
- International and multicultural working environment.
- Very attractive salary.
- Flexible working hours, 8 hours/day, Monday - Friday.
- Opportunities for learning and career advancement.
