Lead Data Engineer

About the role

As a Data Engineer, you’ll feel at home if you are hands on, grounded, opinionated and passionate about delivering comprehensive data solutions that align with modern data architecture approaches. Your work will range from building a full data platform to building data pipelines or helping with data architecture and strategy. This role is ideal for those looking to have a large impact and huge scope for growth, while still being hands on with technology. We aim to allow growth without becoming “post-technical”

Responsibilities

• Collaborate with Data Scientists and Engineers to deliver production quality AI and Machine Learning systems
• Build frameworks and supporting tooling for data ingestion from a complex variety of sources
• Consult with our clients on data strategy, modernising their data infrastructure, architecture and technology
• Model their data for increased visibility and performance
• You will be given ownership of your work, and are encouraged to propose alternatives and make a case for doing things differently; our clients trust us and we manage ourselves.
• You will work in short sprints to deliver working software
• You will be working with other data engineers in Sahaj and work on building Data Engineering capability across the organisation

Skills you’ll need

• Demonstrated experience as a Senior Data Engineer in complex enterprise environments.
• Deep understanding of technology fundamentals and experience with languages like Python, or functional programming languages like Scala
• Demonstrated experience in design and development of big data applications using tech stacks like Databricks, Apache Spark, HDFS, HBase and Snowflake
• Commendable skills in building data products, by integrating large sets of data from hundreds of internal and external sources would be highly critical
• A nuanced understanding of code quality, maintainability and practices like Test Driven Development
• Ability to deliver an application end to end; having an opinion on how your code should be built, packaged and deployed using CI/CD
• Understanding of Cloud platforms, DevOps, GitOps, Containers

Give yourself an opportunity to

• Experience a culture of trust, respect and transparency powered by holacracy.
• An environment that will allow you to hone your craft.
• Collaborate with multi-disciplinary teams to solve some real business problems.
• Solve problems across different domains. Level-up on difficult problems.
• Find your balance between work and life’s ups and downs with unlimited leave when you really need it.
• Not be exploited, as everyone knows everyone’s salary. Radical pay transparency.
• Own what you build. When Sahaj grows in impact and value, you’ll have a share in that upside.

The Lead Data Engineer role focuses on building data platforms, pipelines, and architecture for client and internal needs. It combines hands-on engineering with data strategy, production-quality data products, and collaboration on AI and machine learning systems.

Role at a glance

Skills mentioned

What you will likely work on

• Build data platforms, ingestion frameworks, pipelines, and supporting tools for varied data sources.
• Work with data scientists and engineers to deliver production-ready AI and machine learning systems.
• Advise clients on data strategy and modernizing their data infrastructure, architecture, and technology.
• Model data to improve visibility and performance, including data products integrating large, varied datasets.
• Deliver end-to-end applications, including decisions about building, packaging, and deploying code.
• Work in short sprints to deliver working software and collaborate with other data engineers.
• Help develop data engineering capability across the organization.

Good fit signals

• You have demonstrated experience as a senior data engineer in complex enterprise environments.
• You have developed big data applications and data products that integrate substantial numbers of sources.
• You can deliver applications end to end and make informed choices about code quality, packaging, and deployment.
• You are comfortable advising clients on data architecture and infrastructure modernization.
• You work effectively with data scientists, engineers, and multidisciplinary teams.