About the job
About Indicium AI
Indicium AI stands at the forefront of AI-driven solutions, empowering top global enterprises to harness artificial intelligence efficiently and at scale. As a prominent AI-native consultancy, we specialize in delivering transformative AI strategies across various sectors, including Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing. Our expertise ranges from strategic planning to implementation, ensuring we unlock substantial value from AI with unparalleled clarity and speed.
With a dedicated team of over 600 AI specialists serving more than 50 enterprise clients from five global offices, we collaborate closely with industry leaders such as Anthropic, Databricks, AWS, OpenAI, and Microsoft to drive modern AI solutions with tangible impact.
ABOUT THE ROLE
As a Data Engineer at Indicium AI, you will play a pivotal role in managing essential workstreams during client engagements. You will design and implement robust data solutions in production settings, navigate complex data pipelines with minimal supervision, and contribute to the automation of our infrastructure. Additionally, you will provide technical mentorship to junior team members, directly influencing the data platforms of organizations spanning financial services, retail, energy, and more.
KEY RESPONSIBILITIES
Pipeline Design & Development
- Design, develop, and maintain high-performance ELT pipelines, applying best practices in data engineering.
- Build and oversee data loading processes for both relational and non-relational distributed storage systems.
- Aggregate and transform large datasets utilizing distributed processing technologies such as Spark, Kafka, Presto, or similar.
Infrastructure & Automation
- Provision and sustain data infrastructure using Infrastructure as Code (IaC) tools, primarily Terraform.
- Automate the lifecycle management of infrastructure to ensure consistent adherence to scalability, reliability, and security standards.
Reliability & Governance
- Manage SLA monitoring for data pipelines, proactively identifying and resolving issues in both cloud and on-premises environments.
- Implement data access policies and quality standards in accordance with client governance requirements.
Collaboration & Influence
- Collaborate with analysts, architects, and client stakeholders to effectively translate business needs into sound technical solutions.
- Contribute to technical decision-making processes and promote best practices within the team.
