Senior Data Engineer - AI-Optimized Data Platforms
A
Aimpoint DigitalData and Analytics Consultancy
US and UKFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AWSDockerPythonSQLGCPGitJavaKubernetesSnowflakeAzureSparkCI/CDDevOpsScaladbtDatabricks
Requirements
- Degree educated in Computer Science, Engineering, Mathematics, or equivalent experience
- Experienced at partnering with business stakeholders, explaining technical concepts clearly, and shaping solutions around real business outcomes
- Passionate about modern data engineering and AI trends, including LLM powered analytics, semantic layers, vectorized data access, and metadata-driven architectures
- Strong written and verbal communication skills required
- 3+ years working with relational databases and query languages
- 3+ years building data pipelines in production and ability to work across structured, semi-structured and unstructured data
- 3+ years data modeling (e.g. star schema, entity-relationship)
- 3+ years writing clean, maintainable, and robust code in Python, Scala, Java, or similar coding languages
- 2+ years' experience with dbt Core and/or dbt Cloud preferred
- Experience enabling or accelerating data platform engineering workflows with AI tools such as Codex, Claude, Copilot, Snowflake Cortex Code, and/or Databricks Genie Code preferred
- Comfortable working independently on individual workstream, owning end-to-end delivery from design through production
- Expertise in software engineering concepts and best practices
- DevOps experience preferred
- Experience working with cloud data warehouses (Databricks, Snowflake, Google BigQuery, AWS Redshift, Microsoft Synapse) preferred
- Experience working with cloud ETL/ELT tools (Fivetran, dbt, Matillion, Informatica, Talend, etc.) preferred
- Experience working with cloud platforms (AWS, Azure, GCP) and container technologies (Docker, Kubernetes) preferred
- Experience working with Apache Spark preferred
- Experience preparing data for analytics and following a data science workflow to drive business results preferred
- Consulting experience strongly preferred
- Willingness to travel
Responsibilities
- Become a trusted data and AI advisor to clients, translating business questions into AI-ready data architectures
- Work independently as part of a small team to solve complex data engineering use-cases across various industries
- Design and implement AI-optimized data platforms, including cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytic layers
- Build and evolve semantic and analytical layers that power tools like Snowflake Cortex, Databricks Genie, BI platforms, and emerging AI Copilots
- Use modern platforms and tooling such as Snowflake, Databricks, dbt, Fivetran, and cloud-native orchestration frameworks
- Engineer modern ELT/ETL pipelines that handle structured, semi-structured, and unstructured data to support AI and analytics use cases
- Design modern data models with an emphasis on metrics layers, knowledge graphs, and semantic consistency for AI consumption
- Write production-ready code in SQL, Python, and Spark, following software engineering tools and best-practices such as Git and CI/CD
- Apply AI-assisted data engineering techniques for data exploration, quality checks, schema generation, documentation, lineage, and transformation acceleration
- Contribute to the evolution of the AI-forward data engineering and infrastructure practice, including internal accelerators, patterns, and client-ready architectures
- Collaborate with analytics, data science, and ML project teams to productionize AI-enabled analytics, features, and inference pipelines
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