Indicium AI - Senior Data Engineer
Requirements
• 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 • Databricks and/or Snowflake • 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. • 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.
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.
Benefits
• 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.
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