Principal Technology Architect

**ABOUT JMAN**:
JMAN Group is a growing technology-enabled management consultancy that empowers organizations to create value through data.

Founded in 2010, we are a team of 100+ consultants based in London, UK, and a team of 170+ engineers in Chennai, India. Having delivered multiple projects in the US, we are now opening a new office in New York to help us support and grow our US client base.

We approach business problems with the mindset of a management consultancy and the capabilities of a tech company. We work across all sectors, and have in depth experience in private equity, pharmaceuticals, government departments and high-street chains.

Our team is as cutting edge as our work. We take pride for ourselves on being great to work with - no jargon or corporate-speak, flexible to change and receptive of feedback.

We have a huge focus on investing in the training and professional development of our team, to ensure they can deliver high quality work and shape our journey to becoming a globally recognized brand. The business has grown quickly in the last 3 years with no signs of slowing down.

**Why work at JMAN?**

Our vision is to ensure JMAN Group is the passport to our team’s future. We want our team to go on a fast-paced, high-growth journey with us - when our people want to do something else, the skills, training, exposure, and values that JMAN has instilled in them should open doors all over the world.

**Current Benefits**:

- Competitive annual bonus
- Market-leading private health insurance
- Regular company socials
- Annual company away days
- Extensive training opportunities

**Position**:
**Technical specification**:

- Minimum 5+ years of experience as a Data Architect or similar role, with proven expertise in developing and implementing data strategies.
- Strong understanding and experience with modern data warehouse solutions like Snowflake, Redshift, Synapse, and proficiency in cloud platforms such as AWS, Azure, or GCP preferred.
- Thorough grasp of data governance and security principles, along with experience in data pipelines and ETL/ELT tools, including AWS Glue/Azure Data Factory/Synapse, Matillion/dbt.
- Familiarity with AI/ML platforms and data preparation for ML initiatives is a plus.
- Excellent communication, collaboration, and problem-solving skills are essential.
- Proficiency in Apache Spark or Python programming languages, knowledge of data patterns, data modelling, and product migration.
- Good to have skills include data visualization using Power BI, Tableau, or Looker, and familiarity with full-stack technologies.

**Requirements**:
**Responsibilities**:

- Develop and implement a comprehensive data strategy aligned with business objectives.
- Design and architect a modern data platform using cloud technologies (e.g., AWS, Azure, GCP).
- Build and manage a scalable, secure data warehouse leveraging modern solutions, including implementing data ingestion pipelines for various sources.
- Implement CI/CD pipelines for data pipelines and infrastructure using DevOps tools and methodologies.
- Implement data governance and security best practices to ensure data quality, compliance, and manage metadata.
- Collaborate with cross-functional teams to understand data needs, develop data models, and build analytics tools for reporting, analytics, and AI/ML initiatives.
- Stay updated on emerging data technologies, recommend innovations, and evaluate/recommend cloud data platforms.
- Manage and lead a team of data engineers, providing guidance, monitoring end-to-end operational processes, and overseeing the development and maintenance of data pipelines to ensure quality, reliability, security, and scalability.
- Diagnose existing architecture and data maturity, identifying gaps, proposing solutions, and implementing dimensional modelling and business domain conversion/Data Vault design pattern.

**Other information**:
**Required Skillset**:

- ETL or ELT: AWS Glue/ Azure Data Factory/ Synapse/ Matillion/dbt (Anyone - Mandatory).
- Data Warehouse: Azure SQL Server/Redshift/Big Query/Databricks/Snowflake (Anyone - Mandatory).
- Cloud Experience: AWS/Azure/GCP.
- Quality, Reliability, Security, and Scalability
- Data Pipelines
- SQL and Apache Spark / Python programming languages
- Data Visualization: Power BI/Tableau/Looker. (Anyone-Good to have).
- Full stack technologies (Good to have)
- AI/ML platforms
- Scripting and DevOps tools (e.g., Git, CI/CD pipeline)
- Data Governance.
- Data Modelling.
- Product migration