AWS Data Engineer – Consultant at Deloitte – Johannesburg | Jobyssey

We are looking for an AWS Data Engineer to join our Engineering, AI and Data practice, who is passionate about data and technology solutions, with strong problem-solving and analytical skills, tech savvy with a solid understanding of software development, driven to learn more, keeps up with market evolution and industry trends.

You will have the opportunity to work throughout the entire engagement cycle, specializing in modern data solutions including data ingestion/data pipeline frameworks, data warehouse & data lake architectures, cognitive computing and cloud services.

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.

Behavioural Competencies:

Good communication skills, both written and verbal
Interpersonal and relationship building skills
Desire to develop self
Client delivery focus
Adaptable
Focus on quality
Problem solving ability
Analytical

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

Engineering Competencies:

Able to define a structured approach to problem solving
Completion of data models and designs within client’s architecture and standards
Build robust data pipelines and ETL’s using integration tools and services
Understanding complex business environments and requirements and design a solution based on leading practices
Ability to document design and implement solutions for client product owners
Completion of deliverables for gaining architectural approval at client
Understanding of DataOps approach to solution architecture.
Solid experience in data and SQL is required
Solid data modelling experience

Note: The list of tasks / duties and responsibilities contained in this document is not necessarily exhaustive. Deloitte may ask the employee to carry out additional duties or responsibilities, which may fall reasonably within the ambit of the role profile, depending on operational requirements.

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To help you look out for potential recruitment scams, here are some Red Flags:

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At Deloitte, we want everyone to feel they can be themselves and to thrive at work—in every country, in everything we do, every day. We aim to create a workplace where everyone is treated fairly and with respect, including reasonable accommodation for persons with disabilities.

We are committed to employment equity and building a diverse and inclusive workplace across the African continent. Our recruitment processes are aligned with our Employment Equity Plan and the principles of the Employment Equity Act. Preference may be given to candidates from designated groups.

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