Data Platform Engineer AI Solutions
Summary
Data Platform Engineer at Slalom, a consultancy, building governed data foundations for AI: designing scalable data platforms and reliable batch/streaming pipelines supporting analytics, ML, and Generative AI workloads, with data quality, metadata, lineage, and security. Tools vary by client: Databricks, Snowflake, AWS, Azure, or GCP.
Build governed data foundations for AI at Slalom. This hybrid role supports analytics, machine learning, Generative AI, and agentic workloads.
As a Data Engineer, you will design, build, and operationalize scalable data solutions with clients and delivery teams. The work includes data platforms, reliable pipelines, orchestration, and platform modernization. You may use Databricks, Snowflake, AWS, Azure, or GCP according to client needs.
Key Responsibilities:
- Operationalize data platforms supporting AI and machine learning
- Develop reliable batch and streaming data pipelines
- Enable data quality, metadata, lineage, security, and privacy
- Participate in discovery, design sessions, and code reviews
- Use AI-enabled engineering practices with human review
Requirements:
- Experience with a major cloud or data platform
- Programming proficiency in SQL, Python, Java, or Scala
- Knowledge of ETL, modeling, streaming, or orchestration
- Understanding of responsible engineering for AI-enabled solutions
- Curiosity and willingness to learn new platforms
Bring data engineering experience and responsible AI awareness to Slalom’s client-focused platform and transformation work.
