Head Data Engineer

 

Recruiter:

Datonomy Solutions

Job Ref:

191

Date posted:

Friday, January 8, 2021

Location:

Observatory, South Africa

Salary:

Market related


SUMMARY:
Develop an Advanced Analytics roadmap in collaboration with business stakeholders

POSITION INFO:

Datonomy Solutions is looking for a Head Data Engineer who is passionate about solving business problems with data. This dynamic individual will be responsible for the design/architecture, implementation and support of key datasets that provide structured and timely access to actionable business information, championing the needs of the customer always. This thought leader will use best practices in software engineering, data management, data storage, data compute and distributed systems to solve business problems with data. The Data Engineer will partner with senior leaders in business, operations and technology to drive the improvement in the way that data is stored and consumed. Working in a fast paced environment, this person is an expert in their field and a seasoned professional, delivering results through others over a period of 1 – 3 years.

Data Engineering and Architecture

  • Develop an Advanced Analytics roadmap in collaboration with business stakeholders
  • Develop, innovate and maintain the data architecture that will drive various initiatives across the organisation
  • Provide thought leadership with respect to sustainable data infrastructure 
  • Collaborate with teams to build strategic data models that will help enable the achievement of business outcomes
  • Provide leadership and direction for data engineering and design across multiple projects and functional areas
  • Create robust and automated pipelines to ingest and process data from source systems into analytical platforms using batch and streaming mechanisms 
  • Provides leadership and direction for data engineering and design across multiple projects and functional areas
  • Engineer API’s for returning data to Enterprise Applications
  • Draws on experience with Star Schemas, Data Cubes and Dimensional Models

Data Insight & Analysis

  • Develop data insights to be used for Business Planning, and defining and tracking key business metrics 
  • Creates robust and automated pipelines to ingest and process structured and unstructured data from source systems into analytical platforms 
  • Develop a deep understanding of vast data sources 

Data Management & Support

  • Leverage the right tools for data solutions including leveraging cloud native toolsets
  • Data Management to enable reporting, deep data analysis as well as advanced data science 
  • Building and optimising ‘big data’ data pipelines, architectures and data sets
  • Building processes supporting data transformation, data structures, metadata, dependency and workload management
  • Train and upskill current data capability members on best practices 

Technical Consultation 

  • Partner with senior leaders in business, operations and technology to drive the improvement in the way that data is stored and consumed
  • Advise on performance optimizations and best practices for scalable data models
  • Support application team development by writing stored procedures, functions etc. 
  • Work with scrum team members to estimate and deliver work inside of a sprint 

Data Security Enablement

  • Develop and maintain data security and permissions, including data encryption and database user access controls and logging

Qualifications and Experience

  • Matric
  • Degree in Computer science, database systems, mathematics, business administration, economics or related
  • 5+ years of Data Engineering experience 
  • 7+ years of experience with data warehouse technical architectures, ETL/ELT, and reporting/analytic tools
  • Experience with production implementations in the Cloud
  • Hands on development experience in AWS and Python
  • Experience with Dev/OPS architecture, implementation and operation.
  • Knowledge of Engineering and Operational Excellence using standard methodologies.
  • Extensive experience working with all data warehousing technical components, infrastructure and their integrations


 

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