Data Engineer

MindSource; Plano (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

MindSource is seeking a Junior Data Platform Engineer to design, develop, and implement a modern, scalable data platform in Plano, TX. You will build end-to-end data pipelines using SQL, Python, dbt, and Apache Airflow, migrating Alteryx workflows into code and contributing to AI-driven analytics efforts.

The role focuses on Medallion Architecture (Bronze/Silver/Gold), data modeling, and governance, with on-site collaboration across teams. 3+ years of data engineering experience is required.

Qualifications

• 3+ years in Data Engineering or Data Platform Development.
• Strong SQL with complex queries, performance tuning and optimization.
• Hands-on dbt, including models, incremental strategies and testing.
• Strong Python programming for data processing, automation, and pipelines.

Responsibilities

• Design and develop end-to-end data pipelines from multiple enterprise systems.
• Implement incremental data ingestion and CDC into the Bronze layer.
• Develop and maintain dbt models for cleansing, transformation, and quality validation.
• Build data marts in the Gold layer using Medallion Architecture and dimensional modeling.
• Migrate Alteryx workflows to code-based SQL, dbt, and Python implementations.
• Configure and manage Apache Airflow DAGs for orchestration and scheduling.
• Develop MCP servers to enable AI agents to access data marts.
• Manage data metadata, governance, and lineage with OpenMetadata or similar tooling.
• Automate Excel-based reporting using Python (pandas, openpyxl).
• Collaborate with cross-functional teams to deliver scalable data solutions.

Skills

SQL

Python

dbt

Apache Airflow

Data Modeling

CDC

Kubernetes

Iceberg

Tools

Microsoft SQL Server

Oracle

OpenMetadata

MinIO / S3

Job description

• Job Title: Junior Data Platform Engineer
• Experience: 3+ Years
• Employment Type: Contract
• Work Location: Plano,TX Local candidates only
• Duration: 12 Months

Position Summary

We are seeking a skilled Junior Data Platform Engineer to design, develop, and implement a modern, scalable data platform from the ground up. The ideal candidate will have strong hands‑on experience in SQL, Python, dbt, Apache Airflow, and modern Lakehouse technologies.

In this role, you will build end‑to‑end data pipelines integrating multiple internal business systems using Medallion Architecture (Bronze, Silver, and Gold layers). You will also migrate existing Alteryx workflows into code‑based dbt and Python implementations and contribute to AI‑driven analytics initiatives by developing Model Context Protocol (MCP) servers that enable AI agents to interact with business data.

The ideal candidate should have a strong foundation in data engineering, data modeling, pipeline orchestration, and modern data platform technologies, with an interest in Generative AI and intelligent data applications.

Key Responsibilities

• Design and develop end‑to‑end data pipelines to integrate data from multiple enterprise systems, including Microsoft SQL Server and Oracle.
• Implement incremental data ingestion and Change Data Capture (CDC) mechanisms into the Bronze layer.
• Develop and maintain dbt models for data cleansing, standardization, transformation, deduplication, and data quality validation.
• Build business‑specific data marts in the Gold layer using Medallion Architecture and dimensional data modeling.
• Migrate existing Alteryx workflows into scalable, code‑based SQL, dbt, and Python implementations.
• Configure and manage Apache Iceberg tables and REST Catalog, supporting schema evolution and time‑travel capabilities.
• Develop and maintain Apache Airflow DAGs for workflow orchestration, scheduling, dependency management, and failure notifications.
• Develop MCP servers that enable AI agents to access and query business‑specific data marts.
• Manage data metadata, governance, and lineage using OpenMetadata or similar platforms.
• Automate Excel‑based reporting and business processes using Python, pandas, and openpyxl.
• Collaborate with cross‑functional teams to build reliable, scalable, and governed data solutions.

Required Qualifications

• 3+ years of hands‑on experience in Data Engineering or Data Platform Development.
• Strong SQL skills, including complex queries, CTEs, window functions, and query optimization.
• Hands‑on experience with dbt, including model development, incremental strategies, macros, and testing.
• Strong Python programming skills for data processing, automation, and pipeline development.
• Experience with Python libraries such as pandas.
• Hands‑on experience developing and managing Apache Airflow DAGs.
• Experience with at least one analytical engine: Trino/Presto, Apache Spark, or DuckDB.
• Experience with at least one modern Lakehouse table format: Apache Iceberg, Delta Lake, or Apache Hudi.
• Understanding of Medallion Architecture (Bronze, Silver, and Gold) and dimensional data modeling/star schemas.
• Experience integrating relational databases such as Microsoft SQL Server and Oracle using CDC or batch ingestion methods.
• Familiarity with Kubernetes and S3‑compatible object storage such as MinIO.

Preferred Qualifications

• Experience with data integration tools such as Airbyte or Fivetran.
• Knowledge of Apache Polaris or other Iceberg REST Catalog implementations.
• Experience with data governance and metadata platforms such as OpenMetadata or DataHub.
• Familiarity with semantic layer technologies such as Cube.dev.
• Experience interpreting Alteryx workflows (.yxmd) and migrating transformation logic into SQL/dbt.
• Knowledge of Generative AI, LLM integration, RAG, and AI agent development.
• Hands‑on experience with LangChain and/or LangGraph for building AI agents and multi‑step workflows.
• Experience developing backend applications, APIs, or services using Python and/or Java.
• Familiarity with retail or home appliance business domains, particularly PSI (Production, Sales, and Inventory) and sales analytics.

Required Technical Skills

• SQL
• Python and pandas
• dbt
• Trino/Presto, Apache Spark, or DuckDB
• Apache Iceberg, Delta Lake, or Apache Hudi
• Microsoft SQL Server and Oracle
• MinIO / S3‑compatible storage

Preferred Technical Skills

• MCP Server Development
• Generative AI / LLM Integration
• LangChain and LangGraph
• RAG and AI Agent Workflows
• Airbyte / Fivetran
• OpenMetadata / DataHub
• Cube.dev
• Alteryx
• Java

Ideal Candidate Profile

The ideal candidate is a hands‑on Data Engineer with strong experience building modern data pipelines and lakehouse platforms. Candidates who have worked with dbt, Python, Airflow, and Apache Iceberg or similar technologies will be particularly well suited for this opportunity.

Experience with MCP server development, GenAI, and AI agent integration will be a strong advantage.