# Senior Data Engineer [Indiciumai](https://gurify.com/jobs?q=Indiciumai) · London · Posted 2 days ago Senior [Data](https://gurify.com/jobs/data) [AI & ML](https://gurify.com/jobs/ai-ml) [Apply on the original posting → (opens in a new tab)](https://job-boards.eu.greenhouse.io/indiciumai/jobs/4981580101) ## Job description ### Data Engineer | Senior Consultant ### London ### About Indicium AI Indicium AI is trusted by the world's leading enterprises to deliver AI and data into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from data and AI with unmatched clarity, speed, and capability. Powered by 600+ data, engineering, and AI experts serving 50+ enterprise clients from 5 global locations, we work side-by-side with top partners including Databricks, Snowflake, AWS, Microsoft, Google Cloud, Anthropic, and OpenAI to deliver transformative data and AI solutions that drive measurable business impact. ### Overview We're seeking an experienced Senior Data Engineer to design, build, and scale modern cloud-native data platforms that enable advanced analytics, AI, and business-critical decision making. This role is ideal for someone who enjoys solving complex data challenges end-to-end, from architecting platforms and pipelines through to enabling AI-ready data products. You'll work closely with clients to modernise their data estates, implement best-in-class engineering practices, and deliver scalable data solutions across a variety of cloud environments and technologies. As a consultant, you'll combine deep technical expertise with a pragmatic, outcome-focused mindset, helping enterprise organisations turn their data strategies into reality while influencing engineering best practices across delivery teams. ### Responsibilities - Design and implement modern data platforms, data products, and scalable data pipelines across cloud environments. - Build, optimise, and maintain batch and real-time data processing solutions to support analytics, reporting, machine learning, and AI use cases. - Work with clients to understand business requirements and translate them into robust technical solutions. - Contribute to solution architecture, platform design, and technology selection decisions. - Implement software engineering and DataOps best practices including testing, observability, CI/CD, version control, and infrastructure automation. - Develop and optimise data models, transformations, and storage layers to ensure performance, reliability, and scalability. - Collaborate with cross-functional teams including Data Scientists, AI Engineers, Platform Engineers, Architects, and business stakeholders. - Support clients through discovery, design, delivery, and adoption phases of data transformation programmes. - Mentor engineers and contribute to the growth of engineering capability across project teams. - Contribute to internal initiatives including accelerators, technical communities, blogs, thought leadership, and capability development. ### Required Skills & Experience - Strong hands-on experience building modern data platforms and data products in enterprise environments. - Proven experience with one or more major cloud platforms including AWS, Azure, or Google Cloud Platform. - Proven commercial experience with Databricks and/or Snowflake, including the design, implementation, and optimization of data platforms at scale - Strong SQL expertise and software engineering experience using Python and/or other modern programming languages. - Experience developing and orchestrating data pipelines using technologies such as DBT, Apache Spark, Airflow, Dagster, Kafka, Flink, or equivalent tooling. - Solid understanding of data lakehouse, warehouse, and medallion architecture patterns. - Experience applying DevOps and DataOps best practices including CI/CD, automated testing, monitoring, observability, and release management. - Experience with Infrastructure as Code technologies such as Terraform, Pulumi, CloudFormation, or Bicep. - Strong understanding of distributed systems, data modelling, data governance, security, and performance optimisation. - Ability to engage with technical and non-technical stakeholders, communicating complex concepts in a clear and pragmatic way. - Experience working within consulting, professional services, or client-facing delivery environments. ### Nice to Have - Experience building AI-ready data platforms and supporting GenAI, ML, or advanced analytics workloads. - Experience with real-time streaming architectures and event-driven systems. - Experience with data mesh, data product operating models, or modern data governance frameworks. - Exposure to Data Quality and Observability platforms such as Great Expectations, Monte Carlo, or Soda. - Industry experience within Financial Services, Energy & Utilities, Healthcare, Manufacturing, or Retail. - Cloud provider and/or platform certifications across AWS, Azure, GCP, Databricks, or Snowflake. ### Why Indicium AI - Fast-growing global AI and Data consultancy with significant opportunities for career progression. - Work on high-impact transformation programmes with some of the world's leading enterprises. - Competitive salary and performance-based bonus structure. - Access to leading technologies and strategic partnerships across the AI and Data ecosystem. - Collaborative, low-ego culture where expertise, curiosity, and innovation are valued. - Choose your own equipment, including MacBook, PC, and accessories. - Dedicated learning and development budget to support certifications and continuous growth. - Opportunity to shape the future of a rapidly growing AI-native consultancy. **Live in Indiciumai’s hiring system.** Read from the company's own applicant tracking system, not reposted from a job board — so it's a real, open requisition rather than an ad that outlived the role. We remove it as soon as it disappears at source. ## More jobs like this - PL [Senior Data Engineer (Commercial Analytics)](https://gurify.com/job/senior-data-engineer-commercial-analytics-at-pleo-20f49b17964f) Pleo · London · last week - SO [Data Engineer](https://gurify.com/job/data-engineer-at-solveintelligence-ebf465f19936) Solveintelligence · London · last week - QU [Senior Data Engineer](https://gurify.com/job/senior-data-engineer-at-quantum-fdef49693073) Quantum · London · yesterday - LE [Junior Data Engineer](https://gurify.com/job/junior-data-engineer-at-lendable-d9d9cf24853a) Lendable · London · last week - BL [Graduate Data Engineer](https://gurify.com/job/graduate-data-engineer-at-blenheimchalcot-9f20865a84ff) Blenheimchalcot · London · last week - FO [Graduate Data Engineer](https://gurify.com/job/graduate-data-engineer-at-fosphamarketing-4b8b0ab6d1c9) Fosphamarketing · London · last week ```json {"@context":"https://schema.org/","@type":"JobPosting","title":"Senior Data Engineer","description":"\u003Ch3\u003EData Engineer | Senior Consultant\u003C/h3\u003E\u003Ch3\u003ELondon\u003C/h3\u003E\u003Ch3\u003EAbout Indicium AI\u003C/h3\u003E\u003Cp\u003EIndicium AI is trusted by the world\u0026#39;s leading enterprises to deliver AI and data into production at scale. We are a global AI-native consultancy with proven experience across Financial Services, Energy \u0026amp; Utilities, Healthcare \u0026amp; Life Sciences, Retail \u0026amp; CPG, and Manufacturing. From strategy, to build, to business outcomes, we unlock value from data and AI with unmatched clarity, speed, and capability.\u003C/p\u003E\u003Cp\u003EPowered by 600\u002B data, engineering, and AI experts serving 50\u002B enterprise clients from 5 global locations, we work side-by-side with top partners including Databricks, Snowflake, AWS, Microsoft, Google Cloud, Anthropic, and OpenAI to deliver transformative data and AI solutions that drive measurable business impact.\u003C/p\u003E\u003Ch3\u003EOverview\u003C/h3\u003E\u003Cp\u003EWe\u0026#39;re seeking an experienced Senior Data Engineer to design, build, and scale modern cloud-native data platforms that enable advanced analytics, AI, and business-critical decision making.\u003C/p\u003E\u003Cp\u003EThis role is ideal for someone who enjoys solving complex data challenges end-to-end, from architecting platforms and pipelines through to enabling AI-ready data products. You\u0026#39;ll work closely with clients to modernise their data estates, implement best-in-class engineering practices, and deliver scalable data solutions across a variety of cloud environments and technologies.\u003C/p\u003E\u003Cp\u003EAs a consultant, you\u0026#39;ll combine deep technical expertise with a pragmatic, outcome-focused mindset, helping enterprise organisations turn their data strategies into reality while influencing engineering best practices across delivery teams.\u003C/p\u003E\u003Ch3\u003EResponsibilities\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EDesign and implement modern data platforms, data products, and scalable data pipelines across cloud environments.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EBuild, optimise, and maintain batch and real-time data processing solutions to support analytics, reporting, machine learning, and AI use cases.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EWork with clients to understand business requirements and translate them into robust technical solutions.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EContribute to solution architecture, platform design, and technology selection decisions.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EImplement software engineering and DataOps best practices including testing, observability, CI/CD, version control, and infrastructure automation.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EDevelop and optimise data models, transformations, and storage layers to ensure performance, reliability, and scalability.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ECollaborate with cross-functional teams including Data Scientists, AI Engineers, Platform Engineers, Architects, and business stakeholders.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESupport clients through discovery, design, delivery, and adoption phases of data transformation programmes.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EMentor engineers and contribute to the growth of engineering capability across project teams.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EContribute to internal initiatives including accelerators, technical communities, blogs, thought leadership, and capability development.\u003C/li\u003E\u003C/ul\u003E\u003Ch3\u003ERequired Skills \u0026amp; Experience\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EStrong hands-on experience building modern data platforms and data products in enterprise environments.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EProven experience with one or more major cloud platforms including AWS, Azure, or Google Cloud Platform.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EProven commercial experience with Databricks and/or Snowflake, including the design, implementation, and optimization of data platforms at scale\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EStrong SQL expertise and software engineering experience using Python and/or other modern programming languages.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience developing and orchestrating data pipelines using technologies such as DBT, Apache Spark, Airflow, Dagster, Kafka, Flink, or equivalent tooling.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESolid understanding of data lakehouse, warehouse, and medallion architecture patterns.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience applying DevOps and DataOps best practices including CI/CD, automated testing, monitoring, observability, and release management.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience with Infrastructure as Code technologies such as Terraform, Pulumi, CloudFormation, or Bicep.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EStrong understanding of distributed systems, data modelling, data governance, security, and performance optimisation.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EAbility to engage with technical and non-technical stakeholders, communicating complex concepts in a clear and pragmatic way.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience working within consulting, professional services, or client-facing delivery environments.\u003C/li\u003E\u003C/ul\u003E\u003Ch3\u003ENice to Have\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EExperience building AI-ready data platforms and supporting GenAI, ML, or advanced analytics workloads.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience with real-time streaming architectures and event-driven systems.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience with data mesh, data product operating models, or modern data governance frameworks.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExposure to Data Quality and Observability platforms such as Great Expectations, Monte Carlo, or Soda.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EIndustry experience within Financial Services, Energy \u0026amp; 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