Welcome to MAAS Technologies

Expertise

A team of professionals with deep expertise in thier respective fields.

Innovation

Commitment to staying ahead of technological trends to provide state-of-the-art solutions.

Client-Centric

A focus on understanding and meeting the unique needs of each client.

Quality Assurance

Rigorous quality control processes to ensure top-notch service delivery.

Main Responsibilities:

• Facilitating workshops with stakeholders to elicit business needs and system requirements.
• Documenting 'As is' and 'To be' business processes and system flows.
• Translating business requirements into system (software, platform), process and service requirements.
• Effectively managing business stakeholder expectations throughout the project life cycle.
• Working as the project-lead on the 'scope and define' phase of large projects.
• Providing support and input to the overall definition of the system and UAT test scripts.
• Provide implementation support as and when required, including 'cutover' planning, execution and end-user training. Essential criteria
• You'll need to be proficient in using structured BA methodologies and techniques, including business process modelling, to capture and document requirements, including the "as-is" and "to be".
• You'll need to build and maintain strong relationships with people at all levels. You'll need to make sure projects deliver their intended benefits and that people are ready for the changes.

• You'll need to demonstrate strong experience including on medium and large-scale projects that involve 3rd parties and technical resources.
• You'll need to have experience leading on complex and thorough analysis of system/operational issues before.
• You'll need to communicate complex information in a range of formats and to different audiences.
• You'll need to engage people in our project work, be able to make recommendations, and present arguments fluently and persuasively to achieve goals. Desirable criteria
• Possess a strong understanding of end-to-end project and software development life cycles.
• Are comfortable creating Agile User Stories and Acceptance Criteria.
• Work closely with AI engineers to define end-to-end use cases involving multi-agent AI systems.
• Understading of AI/ML development.
• Help orchestrate tools using OpenAI function calling, vector databases.
• Have excellent Microsoft Office skills (including Visio, ideally with experience of BPMN), and a high-degree of computer literacy.
• Have experience of describing/defining integrations between platforms, through methods such as ETLs or APIs.
• Take a continuous improvement approach to your practices, contributing to the review and introduction of industry best practice, tools and techniques.

What We Offer:

Competitive salary: £45,000 – £50,000
Flexible hybrid work environment
Career development and growth opportunities
A friendly and collaborative work culture

Location:

London (Hybrid working available – a mix of office and remote work)

How to Apply

If you're ready to take your career to the next level and contribute to our success, please send your resume and a cover letter to [email protected]

Main Responsibilities:

• Design, build, and operate simple, repeatable ETL data pipelines within distributed processing environments and cloud platforms, as well as localized single-node processing environments.
• Develop and produce prototyped then productionized code that can be deployed across a range of ETL, data validation, and other data production processes.
• Develop understanding of the native tooling of one or more of: GCP, Azure, AWS.
• An intermediate or better level coding in one or more mainstream coding languages (ie, Python, SQL, Java, Scala, and R), and critically review the code of other data engineers.
• Develop code for a range of data products including data matching, rule development, scans, operational outputs.
• Participate in development and maintenance of in-house code libraries.
• Undertake unit testing to support common code development.
• Review business requirements to ensure they are clear and robust, and transform requirements into reusable production-ready code and/or effective data models.
• Understand the key principles of database design and be able to resolve technical problems in databases, data processes, data products, and services as they occur. Initiate actions, monitor services, and identify trends to resolve problems.
• Apply correct techniques in normalizing data and building robust relational structures in database products.
• Undertake basic data analysis, for example, for data profiling, QA, or problem resolution.
• Support queries from end users on data quality issues affecting data production; communicate issues and blockers to develop solutions.
• Undertake source system analysis and data profiling to confirm data quality and ensure accurate metadata.
• Understand relevant data sources, tools, and systems. Work with experts to develop validation frameworks for both simple and complex data sources.
• Communicate with customers, for example, to update on progress or confirm requirements.
• Using a working knowledge of cloud data engineering tools in assisting with the development of data pipelines, products, and automation processes.
• Work with other team members in development of tool performance logging and monitoring.
• Work with other team members in applying engineering team and community best practice in data products and pipelines.
• Experience predicting and advising on technology changes in the engineering toolset(s) and platform(s) you work on.
• Work with the team in implementing the transition to modern data platforms including Data Warehouse, Lakehouse, across the data products, pipelines, and processes you are responsible for.
• Engage with other professional communities (Data Science, Architecture, etc.) to identify emerging and cross-community issues affecting your role and escalate as necessary.
• Describe technical, data, pipeline, and production issues to colleagues of different specialisms.
• Communicate within the team and across teams to monitor expectations around delivery of data engineering, products, and pipelines, blockers, priorities, and issues. Escalate issues and blockers in delivery proactively.
• Familiar with developing data pipelines and products for very large volume 'big data' series using a range of native engineering tools and practices and coding approaches.
• A working knowledge of engineering standards across a platform and native toolset. Experience implementing these standards in the day-to-day role and keeping outputs up- to-date with these.
• Typical Data Engineering Experience required (5+ years):
• Knowledge and experience of Azure/AWS Cloud data solution provision.
• Proficient in SQL 

• Ability to develop and deliver complex visualisation, reporting and dashboard solutions using tools like Power BI, Informatica
• Enterprise-scale experience with ETL tools (Informatica and or similar).
• Experience of data modelling and transforming raw data into datasets and extracts.
• Experience of working in a large project/scale complex organisation and knowledge of migrating Legacy capabilities.
• Experience in Agile.
• Ability to analyse and collect information and evidence, identify problems and opportunities, and ensure recommendations fit with strategic business objectives.
• Experience of building team capability through role modelling, mentoring, and coaching.
• Ability to manage relationships with non-technical colleagues and can work in a collaborative, inclusive way.
• Ability to design, write, and operate ETL pipelines, in the context of distributed processing, applying coding, data, and documentation standards, in the language required by the business area.
• Understanding of the principles of data processing in a distributed and or cloud platform, and ability to use this understanding to ensure robust coding in a distributed or cloud environment.
• Able to write clean, efficient and well documented code for data processing tasks to a specification.
• Able to use Git for code version control to pull and push and review merge requests for team and own code.
• Ability to undertake simple data and code analysis for effective quality assurance and to resolve processing issues.
• Ability to undertake simple data and code analysis for effective quality assurance and to resolve processing issues.
• Experience of one or more programming/coding languages listed: Python/PySpark, SQL, Proc SQL, NoSQL, MySQL, SQLite, Spark SQL, Hive SQL, PostgreSQL, SAS, SAS E- guide, Scala, RegEx, Java, R
• Investigate problems in systems, processes and services, with an understanding of the level of a problem, for example, strategic, tactical or operational.
• Undertake data profiling and source system analysis for data evaluation, issue resolution or data standardisation.
• Use metadata repositories to complete complex tasks such as data and systems integration impact analysis.
• Good knowledge of database structures, practices, principles of database integrity etc.
• Basic knowledge of applying database principles and SQL coding across a range of platform database and data querying tools (ie SQL Server, Cloud SQL, Big Query, Hive, Athena etc.)
• Show an awareness of opportunities for innovation with new tools and uses of data.
• Experience in more than one of the following tools is required for Engineers engaging in BI development: Plotly, R Shiny, Tableau, QlikView/Qlik sense, Power BI, SAP, Business Objects, MicroStrategy, Snowflake
• Experience of several of the following tools: NiFi, Hbase, Bash, Assist, Putty, Neo4J, Spark, Kafka, HDFS, Oozie, Git Hub, Unix, Hadoop, Impala, DoJo, Flume, Elastic, Logstash, Kibana, Airflow, Glue, Big Query, Athena, CML, Hive, Informatica, CuteFTP Ability to explain and communicate technical concepts in non-technical language.
• Explain the types of communication that can be used with internal and external stakeholders, and their impact.
• Design, build and test data products based on feeds from multiple systems, using a range of different storage technologies, access methods or both.
• Able to explain and implement the concepts and principles of data modelling.
• Ability to create and run simple unit tests.
Desired Qualifications
• Certifications in AWS, Azure, Databricks, or related technologies.
• Experience with public sector data initiatives and compliance requirements.
• Knowledge of machine learning and artificial intelligence concepts.

What We Offer:

Competitive salary: £45,000 – £50,000
Flexible hybrid work environment
Career development and growth opportunities
A friendly and collaborative work culture

Location:

London (Hybrid working available – a mix of office and remote work)

How to Apply

If you're ready to take your career to the next level and contribute to our success, please send your resume and a cover letter to [email protected]