Data Engineer - AWS

AWS Data Engineer – Consultant

Duration: Contract until end of Dec 2026 with possible extension/long term view

Location: Gauteng

Arrangement: Hybrid or Remote

Technical Requirements for the role:

• Support AWS team and implement end-to-end modern data platforms in support of analytics and AI use cases

• Collaborate with enterprise architects, data architects, other ETL developers & engineers, data scientists and information designers to lead identification and definition of required data structures, formats, pipelines, metadata, and workload orchestration capabilities

• Address aspects such as data privacy & security, data ingestion & processing, data storage & compute, analytical & operational consumption, data modelling, data virtualization, self-service data preparation & analytics, AI enablement, and API integrations

• Estimate effort and mentor junior colleagues

• Participate in technical meetings with client staff, and advise client with technical option analyses based on leading practices

• Work as a data engineer on AWS but also on other technologies.

• Apply your deep knowledge of technology to drive continuous improvement.

Qualifications

Bachelor’s Degree (or higher) in quantitative areas such as Computer Science, Information Management, Big Data & Analytics, or related field is desired.

One or more of the following AWS certifications is preferred but experience with building solutions on cloud platforms is mandatory:

• AWS Solutions Architect – Associate/Professional

• AWS Data Engineer Associate

Experience:

• 4+ years’ experience in implementation of creative data solutions leveraging the latest in Big Data frameworks, supporting on-premise or AWS cloud to enable use cases in analytics and AI

• 4+ years’ experience with extraction, transformation and loading of data from a wide variety of traditional and non-traditional sources such as structured, unstructured, and semi-structured using SQL, NoSQL and data pipelines for real-time, streaming, batch and on-demand workloads

• 4+ years’ experience with data warehousing or data lakes.

• Ability to simplify complex technical concepts into easy-to-understand non-technical language in order to facilitate, communicate and interact with executives and business stakeholders, working with Agile development methods in data-oriented projects

Technical Competencies

Must Demonstrate experience in one or more services and technologies listed below:

• Database: SQL Server, NoSQL (Hbase, Cassandra or Mongo DB), Cloud Based Databases (Hive, Cosmos DB, Dynamo DB), Redshift/ Redshift Spectrum, AWS RDS

• Database Development: Experience Views, functions, stored procedures, Optimisation of queries, building indexes, OLAP / MDX

• Cloud: AWS / Azure / GCP /Snowflake (AWS is preferred)

• ETL: AWS Glue, Athena, SSIS, IBM DataStage / SAP Data Services, AWS DMS, Appflow

• Programming: SQL (TSQL /HQL etc), Python, Spark. UNIX & Shell Commands (Python / shell / Perl)

• Modelling: Data Vault, Kimball, 3rd Normal Form / OLAP / MDX)

• Big Data: Hadoop Platform (Cloudera / cloud equivalent), HiveQL /Spark / Ooozie / Impala / Pig), Optimising Big Data, Streaming (NiFi / Kafka)

• Data Acquisition: Pipeline creation, Automation and data delivery, Once off, CDC, Streaming