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Data Engineer

Vaco Financial Dallas Full-Time
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We are searching for a Data Engineer who will be responsible for managing, optimizing, overseeing and monitoring data retrieval, storage and distribution. This person will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The Data Engineer will support software developers, data architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.


  • Develop, construct, test and maintain data platforms and pipelines including enterprise data warehouses and data marts.
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies.
  • Develop data set processes for data modeling, mining, and production.
  • Continuously improve data reliability, efficiency and quality.
  • 3+ years of experience working on large scale, full lifecycle data implementation projects.
  • BS/BA in data engineering, software engineering, data science, computer science, applied mathematics, or equivalent experience.
  • A deep knowledge of performant SQL and understanding of relational database technology.
  • Hands-on RDBMS experience (data modeling, analysis, programming, stored procedures).
  • Expertise in developing ETL/ELT workflows with one or more of the following: Talend/Informatica/InfoSphere ETL tools; Python, Java.
  • Deployment of data pipelines in the Cloud in at least AWS, Azure, or GCP.
  • Proven success working in and promoting a rapidly changing, collaborative, and iterative product development environment.
  • Strong interpersonal and analytical skills.
  • Intellectual curiosity and an ability to execute projects.
  • An understanding of "big picture" business requirements that drive architecture and design decisions.
  • DevOps and DataOps skills including "infrastructure as code" systems.
  • Data system performance tuning.
  • Implementation of predictive analytics and machine learning models (MLlib, scikit-learn, etc).


Recommended skills

Extract Transform Load (Etl)
Extract Transform And Load (Etl)
Data Modeling
Data Science
Performance Tuning
Data Warehousing
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