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Company Overview
A consultancy that helps organizations solve complex data and analytics challenges. They work with clients across various industries, guiding them in their data modernization journeys and helping them unlock the value of their data.
Job Title: Senior Consultant – Data Engineering
What you will be doing
Define and implement end to end data architecture including data pipelines and data models.
Help their clients transition to modern cloud-based infrastructures (AWS, Azure, GCP) and to leverage related architecture patterns (e.g., APIs, events).
Work with their clients in more traditional areas of data engineering such as, data warehousing, building operational ETL/ELT data pipelines across several sources, and constructing relational and dimensional data models.
Define and implement on premise and cloud architectures. Examples of these architectures could be to implement a cloud data warehouse, data lake or a data platform to enable digital transformation.
Perform maturity assessments across their clients’ data capabilities and recommend changes to improve their capabilities.
Your skills and experience
They are looking for experienced consultants (or those with consulting skills gained in industry) who can both advise their clients and, when needed, get hands on in bringing a solution to life.
You must have between 2 and 5 years of experience in hands on data engineering, solution design, and architecture.
Understanding of key core concepts like distributed computing, batch and stream processing, functional and object-orientated programming, how pipelines are built and deployed on cloud, pipeline schedules and SLAs.
Experience of designing and building at least one modern data analytics solution using cloud technologies (Azure, AWS, GCP).
You have expertise in designing robust, scalable solutions and data pipelines to automate the ingestion, processing, orchestration, and delivery of all types of data: structured and unstructured, batch and real-time streaming data.
You understand common data engineering/data architecture patterns and anti-patterns dealing with different types of data.
Capability to complete assigned projects with high degree of autonomy working with key client stakeholders.
You have experience of applying DevOps practices to data engineering, including automated testing, and deployment of specific components (e.g., database changes) using a continuous integration pipeline.
You have worked on big data platforms either on premises or on cloud.
You have experience in using cloud technologies as both infrastructure and as a service.
You have knowledge of building CI/CD pipelines.
Competent in SQL and at least one modern programming language, such a Python.
You are well-versed with documentation and artefacts that needs to go along with the solution design and delivery work. For example, high- and low-level solution design, coding standards, technical specifications, etc.
You hold at least a bachelor’s degree, in any discipline. A master’s degree in a technical discipline (computer science, engineer, or another STEM discipline) would be helpful but is not essential for success.
Disclaimer
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