Blend360
Tech / AI / Software
SrDataEngineering-GCP
Neural analysis suggests this role is
optimal for mid candidates.
“Sr Data Engineering - GCP at Blend360. Skills: Data Engineering, GCP, SQL, Python, data modelling, semantic layer design, scalable data pipelines, AI, ML, LLM. support the delivery of an AI-powered conversational analytics capability. preparing complex business data for AI consumption”
What You'll Achieve.
ensure data is structured for accurate, efficient, and governed querying by LLM-driven workflows; ensure data is accessible, explainable, and aligned to business definitions used in evaluation and user acceptance testing; production readiness
Industry & Context.
What They're Looking For.
Must Have
4+ years of experience in Data Engineering, hands-on experience with SQL and Python for data processing and transformation, Experience building scalable data pipelines and transformation workflows for large, complex datasets, understanding of data modelling, semantic layer design, and analytical data structures, Experience with GCP services such as BigQuery, Pub/Sub, Cloud Run, or Vertex AI, Experience with cloud data platforms such as Databricks or similar, Understanding of governed data access, role-based permissions, and enterprise data standards, Experience supporting AI, ML, or LLM use cases through data preparation, metadata design, or retrieval and query optimisation, Familiarity with testing, validation, and monitoring for data quality and reliability, Experience with Git-based CI/CD development workflows, communication skills and ability to work collaboratively with technical and business stakeholder
Nice to Have
Ideally in cloud-based analytical environments, Experience working with large analytical, transactional, or domain-rich enterprise datasets is highly desirable, Familiarity with semantic modelling for NLP, conversational analytics, or AI-driven querying, Understanding of prompt-aware data design or retrieval-augmented architectures, Experience working in regulated enterprise environments with governance requirements, Experience contributing to knowledge transfer and internal capability enablement
What You'll Do.
support the delivery of an AI-powered conversational analytics capability
preparing complex business data for AI consumption
developing semantic layers
ensuring data is structured for accurate
and governed querying by LLM-driven workflows
and maintain scalable data platforms on Google Cloud
automated data ingestion
analytics engineering
support marketing analytics use cases and BI-driven decision making
enable data-driven insights through robust pipelines
and reporting solutions
and maintain scalable data pipelines to prepare complex business data for conversational analytics use cases
Develop and maintain semantic layers
business logic mappings
and data structures that improve AI understanding of client taxonomies
and business concepts
Model and transform complex business data into structures optimised for query generation
and insight production
Partner with AI and software engineering teams to support LLM workflows
and governed access patterns
Implement robust ingestion
and data quality processes for structured analytical datasets
Support live-query and cached data access patterns depending on agreed architecture and performance needs
Ensure data is accessible
and aligned to business definitions used in evaluation and user acceptance testing
Collaborate with Data Scientists to support ground-truth evaluation
and regression testing
Work with architects and client data stakeholders to align designs with enterprise data standards
governance requirements
and long-term maintainability
Contribute to production readiness through documentation
and knowledge transfer to internal teams
Support deployment of data solutions into controlled Dev
and Production environments
Help shape scalable patterns for future expansion into additional datasets and more advanced analytical capabilities
How You'll Work.
Team & Collaboration
work closely with AI Engineers, Software Engineers, Data Scientists, and DevOps teams; work closely with Data Science, Analytics, and Business teams; Partner with AI and software engineering teams; Collaborate with Data Scientists; Work with architects and client data stakeholders; knowledge transfer to internal teams; work collaboratively with technical and business stakeholder
Communication Scope
communication skills and ability to work collaboratively with technical and business stakeholder
Full Job Description
We are looking for an experienced Senior Data Engineer to support the delivery of an AI-powered conversational analytics capability for a large enterprise client. This role will be critical in preparing complex business data for AI consumption, developing semantic layers, and ensuring data is structured for accurate, efficient, and governed querying by LLM-driven workflows. The ideal candidate will have strong hands-on experience in modern cloud data engineering, data modelling, semantic design, and building scalable pipelines for analytical and AI use cases. This person will work closely with AI Engineers, Software Engineers, Data Scientists, and DevOps teams to ensure the data foundation supports natural language querying, narrative insight generation, anomaly detection, and future scalability. We are looking for a GCP Data Engineer to design, build, and maintain scalable data platforms on Google Cloud. The ideal candidate will have strong experience in automated data ingestion, analytics engineering, and MLOps, with the ability to support marketing analytics use cases and BI-driven decision making. You will work closely with Data Science, Analytics, and Business teams to enable data-driven insights through robust pipelines, models, and reporting solutions. * Design, build, and maintain scalable data pipelines to prepare complex business data for conversational analytics use cases. * Develop and maintain semantic layers, business logic mappings, and data structures that improve AI understanding of client taxonomies, KPIs, hierarchies, and business concepts. * Model and transform complex business data into structures optimised for query generation, interpretation, and insight production. * Partner with AI and software engineering teams to support LLM workflows, agent orchestration, and governed access patterns. * Implement robust ingestion, transformation, and data quality processes for structured analytical datasets. * Support live-query and cached data access pat
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