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Software Data Engineer
Software Data EngineerLink Consulting Services • Plano, TX, US
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Software Data Engineer

Software Data Engineer

Link Consulting Services • Plano, TX, US
[job_card.30_days_ago]
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  • [job_card.full_time]
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Job Description

Job Description

Software Data Engineer

Expected start date : Dec 1st

Duration of engagement : 3 months, with potential extension

Work location : Alpharetta, GA or Plano TX.

Work location model : Hybrid, 3-days in office

About the Role :

The ideal candidate will be responsible for designing and maintaining modern, scalable data solutions on Azure using Databricks. This includes building data pipelines, ETL / ELT workflows, and architectures such as Data Lakes, Warehouses, and Lakehouses for both real-time and batch processing. The role involves integrating large datasets from diverse sources, implementing Delta Lake, and preparing data for machine learning through feature stores.

Key Responsibilities :

  • Design, develop, and optimize scalable data pipelines and ETL / ELT workflows using Databricks on Azure
  • Build and maintain modern data architectures (Data Lake, Data Warehouse, Lakehouse) for real-time streaming and batch processing on Azure
  • Implement data integration solutions for large-scale datasets across diverse data sources using Delta Lake and other data formats
  • Create feature stores and data preparation workflows for machine learning applications on Azure
  • Develop and maintain data quality frameworks and implement data validation checks
  • Collaborate with data scientists, ML engineers, analysts, and business stakeholders to deliver high-quality, production-ready data solutions
  • Monitor, troubleshoot, and optimize data workflows for performance, costefficiency, and reliability
  • Implement data governance, security, and compliance standards across all data processes
  • Create and maintain comprehensive technical documentation for data pipelines and architectures

Required Qualifications :

  • Data Architecture : Deep understanding of Data Lake, Data Warehouse, and Lakehouse concepts with hands-on implementation experience
  • Databricks & Spark : 3+ years of hands-on experience with Databricks on Azure, Apache Spark (PySpark / Spark SQL), Delta Lake optimization
  • Azure Platform : 3+ years working with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure ML Studio, Azure Databricks
  • Programming : Strong proficiency in Python (including pandas, NumPy), SQL, and Unix / Linux shell scripting; experience with Java or Scala is a plus
  • Streaming : 3+ years’ experience with Apache Kafka or Azure Event Hubs, Azure Stream Analytics
  • DevOps : Hands-on experience with Git, CI / CD pipelines (Azure DevOps, GitHub Actions), and build tools (Maven, Gradle)
  • Orchestration : Working knowledge of workflow schedulers (Apache Airflow, Azure Data Factory, Databricks Workflows, TWS)
  • Problem-solving : Strong analytical and debugging skills with ability to work in agile / scrum environments
  • Preferred Qualifications :

  • Experience with ML frameworks and libraries (scikit-learn, TensorFlow, PyTorch) for data preparation and feature engineering on Azure
  • Experience with vector databases (Azure AI Search, Pinecone, Weaviate, Milvus) and RAG (Retrieval Augmented Generation) architectures
  • Experience with modern data transformation tools (DBT, Spark Structured Streaming on Databricks)
  • Understanding of LLM applications, prompt engineering, and AI agent frameworks (Azure OpenAI Service, Semantic Kernel)
  • Familiarity with containerization (Docker, Azure Kubernetes Service)
  • Experience with monitoring and observability tools (Azure Monitor, Application, Insights, Datadog, Grafana)
  • Certifications in Databricks, Azure Data Engineer Associate, Azure AI Engineer, or Azure Solutions Architect
  • Educational Background :

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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