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.