At The AI Training Company, we're not just building AI; we're meticulously teaching it. We're seeking curious, detail-oriented individuals to join our innovative team and play a direct role in training the next generation of artificial intelligence. If you're passionate about shaping the future of technology and want to be at the forefront of AI development by actively training AI models, we want to hear from you. Explore our open roles and help us build smarter AI. #AITrainingJobs #Hiring #AIcareers #MachineLearningOperations #TechJobs #JoinOurTeam

The Ai Training Company

Data Engineers, Analytics Engineers & Data Platform Experts.
We are seeking experienced UK-based Data Engineers, Analytics Engineers, Data Platform Engineers, and Data Architects for an intensive project supporting advanced AI research.
What You’ll Do
Produce realistic data engineering work products based on production workflowsDesign and document ETL and ELT pipelinesBuild data models, transformation logic, and warehouse structuresCreate pipeline architecture documents, implementation plans, and technical specificationsWork with batch and streaming data workflowsDevelop or review orchestration patterns, scheduling logic, and dependency managementProduce SQL and Python-based data engineering solutionsDocument data quality checks, lineage, assumptions, and operational considerationsCreate examples that reflect how experienced data engineers make architectural and implementation decisionsCollaborate with experts from adjacent domains on cross-functional tasksContribute professional judgment that helps define evaluation criteria for advanced AI systems
Who Can Apply
Relevant backgrounds include:
Data Engineers, Senior Data Engineers, Staff Data Engineers, Principal Data Engineers, Lead Data Engineers, Data Engineering Consultants, and Data Engineering Specialists.
We also welcome:
Analytics Engineers, Senior Analytics Engineers, Data Platform Engineers, Data Infrastructure Engineers, Data Systems Engineers, Data Architects, Data Solution Architects, Cloud Data Engineers, and Data Warehouse Engineers.
Pipeline and integration backgrounds may include:
ETL Developers, ETL Engineers, ELT Engineers, Data Integration Engineers, Data Pipeline Engineers, Data Migration Engineers, Data Ingestion Engineers, Data Transformation Engineers, and Data Processing Engineers.
Platform and infrastructure backgrounds may include:
Big Data Engineers, Distributed Data Engineers, Streaming Data Engineers, Data Reliability Engineers, DataOps Engineers, Data Platform Architects, Cloud Data Architects, Data Warehouse Architects, and Data Infrastructure Specialists.
Relevant Data Engineering Experience
Strong candidates may have experience with:
ETL pipelinesELT workflowsBatch processingReal-time and streaming pipelinesData ingestionData transformationData cleansingData validationData quality monitoringData lineageSchema designData modelingDimensional modelingStar and snowflake schemasData warehousesData lakesLakehouse architecturesMedallion architecturesData martsCDC pipelinesEvent-driven data systemsPipeline orchestrationWorkflow schedulingDependency managementBackfills and replayIdempotent pipeline designData observabilityPipeline performance optimizationCost optimizationData governanceProduction incident debugging
Programming & Query Languages
Strong candidates should have hands-on experience with:
SQL and Python
Data Engineering Tools
Experience with one or more of the following is highly relevant:
Apache Spark, PySpark, Kafka, Apache Flink, Apache Beam, Airflow, dbt, Dagster, Prefect, Luigi, Fivetran, Airbyte, Stitch, Matillion, Informatica, Talend, AWS Glue, Azure Data Factory, Google Cloud Dataflow, or similar data integration and orchestration tools.
Warehouses & Data Platforms
Relevant platform experience may include:
Snowflake, Google BigQuery, Databricks, Amazon Redshift, Microsoft Fabric, Azure Synapse Analytics, PostgreSQL, MySQL, SQL Server, Oracle, Teradata, ClickHouse, Trino, Presto, Hive, Delta Lake, Apache Iceberg, and Apache Hudi.
Cloud Experience
Experience across one or more major cloud platforms is valuable:
AWS, Google Cloud Platform, or Microsoft Azure.
Requirements
Professional hands-on experience as a data engineer or closely related roleStrong SQL and Python skillsExperience building and owning production data pipelinesHands-on experience with ETL and/or ELT workflowsExperience with orchestration, data warehousing, and modern data platformsFamiliarity with batch and/or streaming architecturesExperience working with cloud-based data infrastructureStrong understanding of production reliability, data quality, and maintainabilityAbility to create professional technical documentation and work productsStrong written communication and technical judgmentAbility to work independently during a short, intensive engagement
Preferred Background
Senior, Staff, Principal, or Lead-level data engineering experienceExperience owning large-scale production data platformsStrong experience with Spark, Kafka, Airflow, dbt, Snowflake, BigQuery, or DatabricksExperience designing data architecture across AWS, GCP, or AzureExperience with both batch and real-time systemsExperience reviewing or mentoring other data engineersExperience defining data engineering standards or architecture patternsExperience creating design documents, runbooks, data models, or technical specifications
This opportunity is ideal for hands-on UK data engineers who understand how production data systems are actually built, operated, debugged, scaled, and documented, and who can translate that experience into high-quality professional deliverables. We are a referral partner of the client.

Data Engineer | $140/hr | Remote

What the job involves