AWS Data Engineer - Consultant

Requirements

• 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.
• Be careful of Recruitment Scams: Fraudsters or employment scammers often pose as legitimate recruiters, employers, recruitment consultants or job placement firms, advertising false job opportunities through email, text

Additional Information

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

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