ARE YOU OUR NEW CUSTOMER ENGINEER?

 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)

Responsibilities

  • 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!

Customer Engineer