Data Engineer

About JMAN Group

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

Headquartered in London with offices in New York, London, and Chennai, our team of over 450 people blends skills across commercial consulting, data science, and software engineering.

Founded by cousins Anush Newman (Co-founder & CEO) and Leo Valan (Co-founder & CTO), we have grown rapidly since 2019. In May 2023, we took a minority investment from Baird Capital and in January 2024 opened an office in New York aiming to grow our US business to be as large as or bigger than our European business by 2027.

Why work at JMAN

• Our vision is to ensure JMAN Group is the passport to our team’s future.
• Competitive annual bonus
• Market-leading private health insurance
• Regular company socials
• Annual company away days
• Extensive training opportunities

Position

• Strong experience in ETL/ELT or building data pipeline tools like AWS Glue, Azure Data Factory, Synapse, Matillion, dbt.
• Ability to use GIT for version control and maintain versions of data models.
• Hands-on experience in data warehouse/platforms like Azure SQL Server, Redshift, Big Query, Databricks, Snowflake.
• Strong hands-on experience writing SQL queries, database query optimization, and stored procedures.
• Familiarity with data visualization tools like Power BI, Tableau, Looker.
• Ability to integrate with SaaS-based CRM, Accounting, and Financial systems (HubSpot, Salesforce, NetSuite, Zoho).
• Experience in end-to-end deployment from understanding business requirements to implementation.
• Expertise in data solution architectures and data management tools and techniques.
• Constructs and implements operational data store and data marts.
• Strong proficiency in Python and PySpark.
• Knowledge of SDLC and Agile Scrum methodologies.
• Experience with budgeting, service cost, and product migration from legacy to modernized applications.
• Proficiency in SQL and experience with relational databases like MySQL, PostgreSQL.
• Experience with NoSQL databases like MongoDB, Cassandra, or DynamoDB is a plus.
• Strong experience with on-premises and cloud-based databases and lakes.
• Proven experience as a Data Engineer focusing on cloud platforms (AWS, Azure, GCP).
• Experience in full stack technology is a plus.
• Hands-on experience with design patterns, data models, and implementation strategies.
• Extensive internal interfacing including CoE leadership and business units.
• Identify opportunities for automation and implement tools to streamline data engineering workflows.
• Ensure compliance with data governance policies, data privacy regulations, and industry best practices.

Requirements

• Manage and lead a team of data engineers, providing guidance, mentorship, and fostering a collaborative environment.
• Diagnose existing architecture and data maturity and help identify gaps and solutions.
• Build analytics tools utilizing data pipelines for actionable business insights.
• Comply with coding standards and ensure creation of test cases, queries, and validations.
• Evaluate and recommend cloud data platforms for customer needs.
• Provide guidance and monitor end-to-end operational processes.
• Convert data into business domain/entity using Dimensional modelling or Data Vault design pattern.
• Oversee development and maintenance of data pipelines ensuring quality, reliability, security, and scalability.
• Learn and implement evolving open-source technologies for innovative business solutions.
• Build prototypes to test new concepts and promote adoption of new technologies.
• Promote continuous learning and knowledge sharing.
• Design and develop project proposals, technology architecture, delivery management, and career development strategies.
• Strong analytical and critical thinking skills.
• Excellent written and oral communication in English to collaborate with cross-functional teams.

Required Skillset

Primary Skillset

• ETL or ELT: AWS Glue, Azure Data Factory, Synapse, Matillion, dbt (any one mandatory).
• Data Warehouse: Azure SQL Server, Redshift, Big Query, Databricks, Snowflake (any one mandatory).
• Data Patterns.

Secondary Skillset

• Data Visualization: Power BI, Tableau, Looker (good to have).