Data Architect/Engineer

Woongjin•Plano, TX

17h

About The Position

WOONGJIN INC. is seeking a mid-level Data Platform Engineer to build a greenfield data platform that integrates internal systems (GSCM, SEASI, SMART, and BOSS) using Medallion Architecture. The role owns the end-to-end data pipeline, from ingestion through Bronze, Silver, and Gold transformations, and migrates existing Alteryx workflows to code-based dbt and Python implementations. The engineer will also develop an MCP server so AI agents can query business-specific data marts, supporting AI-driven analytics initiatives. The goal is to deliver a scalable, governed data foundation that accelerates business insights and AI adoption. The role includes ingesting and transforming data, developing and operating Airflow workflows, configuring lakehouse tables and catalogs, managing metadata and lineage, and automating Excel reporting. The position also works with analytical engines, relational database sources, and AI-agent tooling.

Requirements

At least 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 listed: 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, and MinIO (S3-compatible storage).

Nice To Haves

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.
Preferred technical skills listed: 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, and openpyxl.

Responsibilities

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 and metadata access, ontology integration, and query execution.
Manage metadata and data lineage using OpenMetadata.
Automate Excel reporting using Python and openpyxl.