About the job
About Indicium AI
Indicium AI is a premier global consultancy renowned for integrating AI into production at scale. We partner with some of the world’s foremost enterprises across various sectors, including Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. Our mission is to unlock the potential of AI, facilitating strategic implementation through speed, clarity, and unparalleled capability.
With a dedicated team of over 600 AI experts, we serve more than 50 enterprise clients across five global offices. Collaborating with industry leaders such as Anthropic, Databricks, AWS, OpenAI, and Microsoft, we drive modern AI solutions that yield tangible results.
Opportunity
We are eager to connect with individuals possessing a robust data background and cloud-native skills, particularly those experienced in delivering high-quality software solutions. As a consulting firm focused on outcomes, we seek professionals who embrace a consultative approach to problem-solving in a comprehensive, end-to-end manner. Join our diverse, talented team to share knowledge and learn from varied experiences.
Responsibilities
- Lead the technical implementation and delivery of advanced data systems and AI-enabled applications.
- Address end-to-end data challenges and identify opportunities at scale.
- Contribute to the architecture and design of innovative solutions.
- Collaborate with clients to bring their data strategies to fruition.
- Work with your cross-functional team throughout all phases of engagement, including advisory, design, and implementation of comprehensive solutions.
- Participate in internal initiatives, such as writing blogs and engaging in technical forums.
Requirements
- Strong understanding of modern data engineering concepts (e.g., distributed systems, data streaming, event-based architectures).
- Experience with software engineering and DevOps best practices, encompassing the entire software development lifecycle (SDLC) applied to data: automation, testing, contract definition, clean code, CI/CD, and path to production.
- Familiarity with one or more cloud platforms and services such as AWS, Azure, or GCP.
- Extensive hands-on experience with contemporary data technologies and ETL tools (e.g., Kafka, Flink, DBT) and data storage solutions (e.g., Snowflake, Redshift).

