Let’s get down to details

Datisan has a newly created role for a Customer Engineer, to play a part in our growing data team.

The Customer Engineer is a critical function within the Datisan team leading client facing interactions, providing leadership and technical guidance with cloud architecture and ecosystem integration.

You will also provide technical pre-sales support to the CEO and Sales team, where needed.

  • Develop technical solutions and write code for the extraction of data and the integration of disparate data sources
  • Develop against platform APIs for integration in the GCP environment
  • Product & data integrity testing
  • Work closely with other team members to provide the best outcomes for our clients

You will thrive in this role!

If you are..

  • Highly motivated and delivery focused thought leader.
  • 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.

Do I have the skills to fit the bill?

Minimum Qualifications

  • Experience in big data, SaaS/PaaS/IaaS technologies, web development, DevOps infrastructure, enterprise networking, or virtualization/migration/configuration management.
  • 2 – 3 years of experience in technical pre-sales or customer-facing solutions in a cloud computing environment.
  • 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.
  • Previous experience managing and working with offshore teams.

What else do you need?

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 haves

  • 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)


  • Use cloud-first serverless approaches to solve client’s data ingestion, processing & storage needs
  • Develop, construct, test, and maintain data ingestion & warehousing architectures
  • Build high-performance algorithms, prototypes, predictive models and proof of concepts
  • Discover opportunities for data acquisition and new uses for existing data
  • Develop dataset processes for data modeling, mining and production
  • Employ a variety of languages and tools (e.g. scripting languages) to marry systems together
  • Recommend ways to improve data reliability, efficiency and quality
  • Supporting the CTO and CEO with technical presales activities
  • Demonstrate prototype integrations for Google Cloud’s products in customer/partner environments.
  • Work with the CTO and CEO to prepare and deliver product messaging to highlight Datisan’s value proposition.
  • Make recommendations on integration strategies, enterprise architectures, platforms and application infrastructure to successfully implement a complete solution, providing “best practice” advice to clients.
  • Understand and translate complex business requirements into a functional technical architecture that can be implemented and activated by clients. Manage delivery of solutions by working collaboratively with Google GCP teams, Datisan teams, and delivery partners.
  • Develop and maintain product knowledge about core competencies of Google technologies, and other industry technology solutions. 
  • Document the current state of the client’s technology and outline systems enhancements needed. Serve as technical leader for Datisan’s clients, with regards to Cloud Solutions.
  • Develop deep business partnerships and trusted relationships with both partners and decision-makers at the C-suite level.

What does Datisan offer?

Great question! so glad you asked

  • 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.
  • Great work space with other team members from various industries & disciplines
  • 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!
  • No office slippery slides, but our clients have them. There is darts & we “live” upstairs from a brewery – just sayin’

Check our social accounts to see what we’re up to right now!

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