Data Engineer

Company Description

JMAN Group is a fast-growing data engineering & data science consultancy. We work primarily with Private Equity Funds and their Portfolio Companies to create commercial value using Data & Artificial Intelligence. In addition, we also work with growth businesses, large corporates, multinationals, and charities.

We are headquartered in London with Offices in New York, London and Chennai. Our team of over 450 people is a unique blend of individuals with skills across commercial consulting, data science and software engineering.

We were founded by cousins Anush Newman (Co-founder & CEO) and Leo Valan (Co-founder & CTO) and have grown rapidly since 2019. In May 2023 we took a minority investment from Baird Capital and in January 2024 we opened an office in New York with the ambition of growing our US business to be as large as, if not bigger than, our European business by 2027.

Technical specifications

• 2 + years of experience in data platform builds.
• Familiarity with multi cloud data warehousing solutions (Snowflake, Redshift, Databricks, Fabric, AWS Glue, Azure Data Factory, Synapse, Matillion,DBT ).
• Proficient in SQL, Apache Spark / Python programming languages.
• Good to have skills includes Data visualization using Power BI, Tableau, or Looker, and familiarity with full-stack technologies.
• Experience with containerization technologies (e.g., Docker, Kubernetes)
• Experience with CI / CD pipelines and DevOps methodologies.
• Ability to work independently, adapt to changing priorities, and learn new technologies quickly.
• Experience in implementing or working with data governance frameworks and practices to ensure data integrity and regulatory compliance.
• Knowledge of data quality tools and practices.

Responsibilities

Requirements

Required Skillset :

ETL or ELT : AWS Glue / Azure Data Factory / Synapse / Matillion / dbt.

Data Warehousing : Azure SQL Server / Redshift / Big Query / Databricks / Snowflake / fabric (Anyone - Mandatory).

Data Visualization : Looker, Power BI, Tableau.

SQL and Apache Spark / Python programming languages

Containerization technologies (e.g., Docker, Kubernetes)

Cloud Experience : AWS / Azure / GCP.

Scripting and DevOps tools (e.g., Git, CI / CD pipeline)