A client in the automobile industry is looking for a AWS Data Engineer (Senior)

Product / Feature Team Information (if applicable)
Our Domain, Enterprise Data Services, Platforms, comprises of a number of Data Business Objects, namely, Quality, Motorbike, Purchasing & Supplier, Marketing & Research, Finance, Sales, Customer, Customer Support, ITO and OTD
ESSENTIAL SKILLS REQUIREMENTS:
Above average experience/understanding (in order of importance):
e.g. Technical Skills / Technology

• Terraform
• Python 3x
• SQL - Oracle/PostgreSQL
• Py Spark
• Boto3
• ETL
• Docker
• Linux / Unix
• Big Data
• Powershell / Bash

Basic experience/understanding of AWS Components (in order of importance):

• Glue
• CloudWatch
• SNS
• Athena
• S3
• Kinesis Streams (Kinesis, Kinesis Firehose)
• Lambda
• DynamoDB
• Step Function
• Param Store
• Secrets Manager
• Code Build/Pipeline
• CloudFormation
• Business Intelligence (BI) Experience
• Technical data modelling and schema design (“not drag and drop”)
• Kafka 

·        AWS EMR
·        Redshift
 
·        Experience in working with Enterprise Collaboration tools such as Confluence, JIRA etc.
·        Experience developing technical documentation and artefacts.
·        Knowledge of data formats such as Parquet, AVRO, JSON, XML, CSV etc.
·        Experience working with Data Quality Tools such as Great Expectations.
·        Experience developing and working with REST API's is a bonus.
 
·        Basic experience in Networking and troubleshooting network issues.
·        Any additional responsibilities assigned in the Agile Working Model (AWM) Charter
ADVANTAGEOUS SKILLS REQUIREMENTS:
·        Demonstrate expertise in data modelling Oracle SQL.
·        Exceptional analytical skills analysing large and complex data sets.
·        Perform thorough testing and data validation to ensure the accuracy of data transformations.
·        Strong written and verbal communication skills, with precise documentation.
·        Self-driven team player with ability to work independently and multi-task.
·        Experience building data pipeline using AWS Glue or Data Pipeline, or similar platforms.
·        Familiar with data store such as AWS S3, and AWS RDS or DynamoDB.
·        Experience and solid understanding of various software design patterns.
·        Experience preparing specifications from which programs will be written, designed, coded, tested and debugged.
·        Strong organizational skills.
WHICH QUALIFICATIONS/EXPERIENCE DO WE NEED FOR THE ROLE?
·        Relevant IT / Business / Engineering Degree
Certifications:
·        Candidates with one or more of the certifications are preferred.
·        AWS Certified Cloud Practitioner, AWS Certified SysOps Associate, AWS Certified Developer Associate, AWS Certified Architect Associate, AWS Certified Architect Professional, Hashicorp Certified Terraform Associate
WHAT WILL BE YOUR ROLE AND RESPONSIBILITIES?
e.g. Core Role tasks and responsibilities
Data Engineers are responsible for building and maintaining Big Data Pipelines using Data Platforms. Data Engineers are custodians of data and must ensure that data is shared in line with the information classification requirements on a need-to-know basis.
Data Engineers are also expected to:
Stay up to date with the latest data engineering tools, technologies and industry trends. Identify opportunities for process improvements and automation to enhance the efficiency and reliability of data pipelines. Explore and evaluate new data engineering approaches and technologies to drive innovation within the organisation.

Mentor, train and upskill members in the team.
 
WHAT DO WE OFFER YOU?
·        Cutting edge global IT system landscape and processes
·        Flexible working of 1960 hours in a 12-month period
·        High Work-Life balance
·        Remote / On-site work location flexibility
·        Affordable Group vehicle promotions (buying or leasing options available, terms and conditions apply)
·        Highly motivating, energetic, and fast-paced working environment
·        Modern, state-of-the-art offices
·        Dynamic Global Team collaboration
·        Application of the Agile Working Model Methodology