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Junior Data Architect/Engineer

Plano, TX, United States

Pay
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Work setting
On-site — work setting source
Work setup in the employer’s listing: On-site
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Employment
Full-time — employment source
Employment type in the employer’s listing: Full-time
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Apply at SBT Global

What you’ll bring

All qualifications

Core experience

  • 3+ years of hands-on data engineering experience in production environments
  • Python proficiency for data processing and automation, including libraries such as pandas
  • Experience developing Apache Airflow DAGs
  • Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB
  • Experience with at least one lakehouse table format: Apache Iceberg, Delta Lake, or Apache Hudi
  • Experience with Medallion Architecture and star schema/dimensional modeling

Preferred experience

  • Experience with EL tools such as Airbyte or Fivetran, and Iceberg REST Catalog implementations such as Apache Polaris
  • Experience with governance tools such as OpenMetadata or DataHub, and semantic layers such as Cube.dev
  • Ability to interpret Alteryx workflows (.yxmd) and migrate their logic to SQL/dbt
  • Experience developing MCP servers or building LLM, RAG, or AI agent pipelines
Qualification wording
3+ years of hands-on data engineering experience in production environments
Python proficiency for data processing and automation, including libraries such as pandas
Experience developing Apache Airflow DAGs
Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB
Experience with at least one lakehouse table format: Apache Iceberg, Delta Lake, or Apache Hudi
Experience with Medallion Architecture and star schema/dimensional modeling
Experience with EL tools such as Airbyte or Fivetran, and Iceberg REST Catalog implementations such as Apache Polaris
Experience with governance tools such as OpenMetadata or DataHub, and semantic layers such as Cube.dev
Ability to interpret Alteryx workflows (.yxmd) and migrate their logic to SQL/dbt
Experience developing MCP servers or building LLM, RAG, or AI agent pipelines

Tools in this posting

  • Java
  • Python
  • SQL
  • Airbyte
  • dbt
  • Delta Lake
  • DuckDB
  • Fivetran
  • Iceberg
  • Kubernetes
  • Oracle
  • S3
  • Spark
  • SQL Server
  • Trino
  • Airflow
  • pandas
Source — Tool mentions in context
- Experience developing MCP servers or building LLM, RAG, or AI agent pipelines - Experience developing applications, APIs, or backend services using Java and/or Python - Experience building Generative AI (GenAI) applications, including LLM integration, retrieval-augmented generation (RAG), and AI agent workflows
Preferred Technical Skills - Java or Python - Generative AI (GenAI) and LLM integration
- Manage metadata and data lineage using OpenMetadata - Automate Excel reporting using Python and openpyxl Qualifications
- Hands-on dbt experience, including model design, incremental strategies, macros, and tests - Python proficiency for data processing and automation, including libraries such as pandas - Experience developing Apache Airflow DAGs
- dbt - Python - pandas
We are seeking a mid-level Data Platform Engineer to build a new greenfield data platform integrating internal systems (GSCM, SEASI, SMART, and BOSS) using a Medallion Architecture. This role owns the end-to-end data pipeline—from ingestion through Bronze/Silver/Gold transformation—while migrating existing Alteryx workflows to code-based dbt and Python implementations. The engineer will also develop an MCP server enabling AI agents to query business-specific data marts, directly supporting the organization's AI-driven analytics initiatives.
Job Description - Ingest data from sources such as Microsoft SQL Server (BOSS) and Oracle into the Bronze layer, implementing CDC-based incremental ingestion - Develop dbt models for the Silver layer including cleansing, standardization, deduplication, and data quality testing
- 3+ years of hands-on data engineering experience in production environments - Advanced SQL skills, including window functions, CTEs, and query tuning - Hands-on dbt experience, including model design, incremental strategies, macros, and tests
- Experience with Medallion Architecture and star schema/dimensional modeling - Experience integrating relational database sources, such as Microsoft SQL Server and Oracle, using CDC or batch processing Required Technical Skills
Required Technical Skills - SQL - dbt
- Apache Iceberg or Delta Lake or Apache Hudi - Microsoft SQL Server - Oracle
- Experience with governance tools such as OpenMetadata or DataHub, and semantic layers such as Cube.dev - Ability to interpret Alteryx workflows (.yxmd) and migrate their logic to SQL/dbt - Experience developing MCP servers or building LLM, RAG, or AI agent pipelines
Preferred Qualifications - Experience with EL tools such as Airbyte or Fivetran, and Iceberg REST Catalog implementations such as Apache Polaris - Experience with governance tools such as OpenMetadata or DataHub, and semantic layers such as Cube.dev
- MCP server development - Airbyte - Fivetran
- Ingest data from sources such as Microsoft SQL Server (BOSS) and Oracle into the Bronze layer, implementing CDC-based incremental ingestion - Develop dbt models for the Silver layer including cleansing, standardization, deduplication, and data quality testing - Develop Gold layer business-specific data marts and migrate existing Alteryx transformation logic
- Advanced SQL skills, including window functions, CTEs, and query tuning - Hands-on dbt experience, including model design, incremental strategies, macros, and tests - Python proficiency for data processing and automation, including libraries such as pandas
- SQL - dbt - Python
- Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB - Experience with at least one lakehouse table format: Apache Iceberg, Delta Lake, or Apache Hudi - Experience with Medallion Architecture and star schema/dimensional modeling
- Trino/Presto or Apache Spark or DuckDB - Apache Iceberg or Delta Lake or Apache Hudi - Microsoft SQL Server
- Experience developing Apache Airflow DAGs - Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB - Experience with at least one lakehouse table format: Apache Iceberg, Delta Lake, or Apache Hudi
- Apache Airflow - Trino/Presto or Apache Spark or DuckDB - Apache Iceberg or Delta Lake or Apache Hudi
- Airbyte - Fivetran - Apache Polaris
- Develop Gold layer business-specific data marts and migrate existing Alteryx transformation logic - Configure Apache Iceberg tables and a REST Catalog, including schema evolution and time travel support - Develop and operate Apache Airflow DAGs, managing dependencies, scheduling, and failure notifications
- Oracle - Kubernetes - MinIO (S3-compatible storage)
- Microsoft SQL Server - Oracle - Kubernetes
- Kubernetes - MinIO (S3-compatible storage) Preferred Qualifications
- Configure Apache Iceberg tables and a REST Catalog, including schema evolution and time travel support - Develop and operate Apache Airflow DAGs, managing dependencies, scheduling, and failure notifications - Develop an MCP server enabling AI agents to query Gold-layer data marts, including catalog/metadata access, ontology integration, and query execution
- Python proficiency for data processing and automation, including libraries such as pandas - Experience developing Apache Airflow DAGs - Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB
- pandas - Apache Airflow - Trino/Presto or Apache Spark or DuckDB
- Python - pandas - Apache Airflow

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Job description

View original posting ↗

Job Description

  • Ingest data from sources such as Microsoft SQL Server (BOSS) and Oracle into the Bronze layer, implementing CDC-based incremental ingestion

  • Develop dbt models for the Silver layer including cleansing, standardization, deduplication, and data quality testing

  • Develop Gold layer business-specific data marts and migrate existing Alteryx transformation logic

  • Configure Apache Iceberg tables and a REST Catalog, including schema evolution and time travel support

  • Develop and operate Apache Airflow DAGs, managing dependencies, scheduling, and failure notifications

  • Develop an MCP server enabling AI agents to query Gold-layer data marts, including catalog/metadata access, ontology integration, and query execution

  • Manage metadata and data lineage using OpenMetadata

  • Automate Excel reporting using Python and openpyxl

Qualifications

  • 3+ years of hands-on data engineering experience in production environments

  • Advanced SQL skills, including window functions, CTEs, and query tuning

  • Hands-on dbt experience, including model design, incremental strategies, macros, and tests

  • Python proficiency for data processing and automation, including libraries such as pandas

  • Experience developing Apache Airflow DAGs

  • Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB

  • Experience with at least one lakehouse table format: Apache Iceberg, Delta Lake, or Apache Hudi

  • Experience with Medallion Architecture and star schema/dimensional modeling

  • Experience integrating relational database sources, such as Microsoft SQL Server and Oracle, using CDC or batch processing

 

Required Technical Skills

  • SQL

  • dbt

  • Python

  • pandas

  • Apache Airflow

  • Trino/Presto or Apache Spark or DuckDB

  • Apache Iceberg or Delta Lake or Apache Hudi

  • Microsoft SQL Server

  • Oracle

  • Kubernetes

  • MinIO (S3-compatible storage)

 

Preferred Qualifications

  • Experience with EL tools such as Airbyte or Fivetran, and Iceberg REST Catalog implementations such as Apache Polaris

  • Experience with governance tools such as OpenMetadata or DataHub, and semantic layers such as Cube.dev

  • Ability to interpret Alteryx workflows (.yxmd) and migrate their logic to SQL/dbt

  • Experience developing MCP servers or building LLM, RAG, or AI agent pipelines

  • Experience developing applications, APIs, or backend services using Java and/or Python

  • Experience building Generative AI (GenAI) applications, including LLM integration, retrieval-augmented generation (RAG), and AI agent workflows

  • Hands-on experience with LangChain and/or LangGraph for developing tool-enabled AI agents and orchestrating multi-step workflows

  • Understanding of retail and home appliance business domains, including PSI (Production, Sales, and Inventory) and sales analytics

  • Understanding of retail and home appliance business domains, including PSI (Production, Sales, and Inventory) and sales analytics

 

Preferred Technical Skills

  • Java or Python

  • Generative AI (GenAI) and LLM integration

  • LangChain

  • LangGraph

  • RAG and AI agent pipelines

  • MCP server development

  • Airbyte

  • Fivetran

  • Apache Polaris

  • OpenMetadata

  • DataHub

  • Cube.dev

  • Alteryx

  • openpyxl

Additional Information

All your information will be kept confidential according to EEO guidelines.

Company Description

Payrate: $10,400/m DOE

Work Location: Plano, TX

Contract Period: 1 year

 

We are seeking a mid-level Data Platform Engineer to build a new greenfield data platform integrating internal systems (GSCM, SEASI, SMART, and BOSS) using a Medallion Architecture.

This role owns the end-to-end data pipeline—from ingestion through Bronze/Silver/Gold transformation—while migrating existing Alteryx workflows to code-based dbt and Python implementations.

The engineer will also develop an MCP server enabling AI agents to query business-specific data marts, directly supporting the organization's AI-driven analytics initiatives.

Success in this role will deliver a scalable, governed data foundation that accelerates business insights and AI adoption.

Source details

View original posting ↗

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Plano, TX, United States

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