Role Profile:

Working with data software engineers, product managers, Data Ops and data scientists to build data architecture that drives insights

Drive data cost efficiency with good data model design, minimized data replication, and cost-effective storage and usage

Lead the data engineering best practice inputs to data architecture (principles and adoption of MACH approaches), data security, data automation Ensure data security protocols are aligned to policy and operational

Ensure data architecture requirements are implemented, documented and operational

Designing and building reusable components, frameworks, and libraries at scale to support analytics data products

Improving processes regarding data flow and quality to improve data accuracy, viability, and value

Identifying, designing, and implementing process improvements that include building/re-engineering data models, data architectures, pipelines, and data applications

Continuously look for data optimization processes and oversee data management, governance, security, and analysis

Increase automation and build analytic solutions at scale to serve the business requirements

 

The below Key Performance Areas include but are not limited to:

Data engineering: ETL/ELT design and build for data batching and streaming; data standardisation and reference data management; able to leverage data automation methods to provide data-as-a-service; deliver data lineage operation and optimization

Hands-on experience analyzing, architecting/re-architecting data and analytics platforms on AWS/GCP or similar platform

Test-driven development: able to build pipelines, data transformations and business rules for data management using Python and/or Spark. Able to identify, recruit, train and retain the necessary team to manage data engineering work at Alshaya

Experience in designing and implementing data ingestion solutions on AWS or GCP using different approaches

Must have experience designing and architecting data lakes on cloud platforms and BI application integrations.

Knowledge of data security best practices and experience building secure data solutions

Experience designing and setting up a lakehouse architecture using Databricks or any similar technologies  

Knowledge of data visualizations and self-service data preparation tools to maintain the flow of data for the analytics and visualization teams

 

Collab/management: Lead a team of Data Engineers, Devops, Business Analysts

Experience managing engineers and guiding them through project planning, design, development, quality control, and deployment

Mentorship and career growth where you will be responsible for 121’s, Goal setting, career development, code reviews

 

Knowledge (Desired):

Experience Lead a team of data engineers and guide them with the best data strategies in line with data needs

Identifying, designing, and implementing process improvements that include building/re-engineering data models, data architectures, pipelines, and data applications

Continuously look for data optimization processes and oversee data management, governance, security, and analysis

Hire the best talents, identify the potential of each team member and offer technical guidance, leadership, and advice on planning, designing, and implementing data solutions

Ensure data quality and security across every product vertical and related areas

Design, create and launch new data models and pipelines as per needs

Work towards achieving high performance, operational excellence, accuracy, and reliability of the overall system

Utilize tools and technologies to create data architecture that supports new data initiatives and is useful in next-gen products

Ensure test-driven products/pipelines that are easily maintainable and reusable

Design and build an infrastructure for extraction, transformation, and loading of data from a wide range of data sources

Overall build and maintain data foundations that include tools, infrastructure, and pipelines that help the marketing and sales team

Increase automation and build analytic solutions at scale to serve the business requirements

Behaviours:

- must show commitment to continuous skills improvement / self-learning

- strong demonstration of timeliness and delivering to commitments

- demonstrated collaborative approach to work

- empathetic to our customers and their needs & wants

- culturally aligned to Alshaya values

- start-up mindset: we are developing a new capability for the enterprise