Aws data engineer - consultant
Company Description
At Deloitte, our Purpose is to make an impact that matters for our clients, our people, and society. This is the lens for which our global strategy is set. It unites Deloitte professionals across geographies, businesses, and skills. It makes us better at what we do and how we do it. It enables us to deliver on our promises to stakeholders, while creating the lasting impact we seek.
Harnessing the talent of 450,000+ people located across more than 150 countries and territories, our size and scale puts us in a unique position to help change the world for the better—by bringing together the services we provide, the societal investments we make, and the collaborations we advance through our ecosystems.
Deloitte offers career opportunities across Audit & Assurance (A&A), Tax & Legal (T&L) and our Consulting services business, which is made up of Strategy, Risk & Transactions Advisory (SR&T) and Technology & Transformation (T&T).
Engineering AI and Data Engineering AI and Data forms part of our Consulting Services business. We require a Consultant with proven consulting expertise developing and recommending appropriate system solutions for clients, with a primary focus on the SAP solution suite of applications. The applicant will support relevant service area leadership with market development initiatives through driving and implementation of strategy, revenue generation and business growth, whilst supporting project teams at clients with work assignments.
Job Description 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
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, No SQL 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
Database: SQL Server, No SQL (Hbase, Cassandra or Mongo DB), Cloud Based Databases (Hive, Cosmos DB, Dynamo DB), Redshift / Redshift Spectrum, AWS RDS
Database Development: Experience with 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 Data Stage / 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), Hive QL / Spark / Oozie / Impala / Pig, Optimising Big Data, Streaming (Ni Fi / 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 Data Ops approach to solution architecture.
Solid experience in data and SQL is required
Solid data modelling experience
Additional Information 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.
Equal Employment Opportunity At Deloitte, we want everyone to feel they can be themselves and 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.
We actively support the inclusion of people with disabilities and embrace neurodiversity in the workplace. We recognise and value the unique strengths that neurodivergent individuals bring, and we are committed to creating an environment where everyone can thrive.
If you require reasonable accommodations in relation to your disability and neurodiverse needs during the recruitment process, please let us know. We are happy to make adjustments to suit your individual needs.
Harnessing the talent of 450,000+ people located across more than 150 countries and territories, our size and scale puts us in a unique position to help change the world for the better—by bringing together the services we provide, the societal investments we make, and the collaborations we advance through our ecosystems.
Deloitte offers career opportunities across Audit & Assurance (A&A), Tax & Legal (T&L) and our Consulting services business, which is made up of Strategy, Risk & Transactions Advisory (SR&T) and Technology & Transformation (T&T).
Engineering AI and Data Engineering AI and Data forms part of our Consulting Services business. We require a Consultant with proven consulting expertise developing and recommending appropriate system solutions for clients, with a primary focus on the SAP solution suite of applications. The applicant will support relevant service area leadership with market development initiatives through driving and implementation of strategy, revenue generation and business growth, whilst supporting project teams at clients with work assignments.
Job Description 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
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, No SQL 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
Database: SQL Server, No SQL (Hbase, Cassandra or Mongo DB), Cloud Based Databases (Hive, Cosmos DB, Dynamo DB), Redshift / Redshift Spectrum, AWS RDS
Database Development: Experience with 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 Data Stage / 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), Hive QL / Spark / Oozie / Impala / Pig, Optimising Big Data, Streaming (Ni Fi / 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 Data Ops approach to solution architecture.
Solid experience in data and SQL is required
Solid data modelling experience
Additional Information 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.
Equal Employment Opportunity At Deloitte, we want everyone to feel they can be themselves and 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.
We actively support the inclusion of people with disabilities and embrace neurodiversity in the workplace. We recognise and value the unique strengths that neurodivergent individuals bring, and we are committed to creating an environment where everyone can thrive.
If you require reasonable accommodations in relation to your disability and neurodiverse needs during the recruitment process, please let us know. We are happy to make adjustments to suit your individual needs.