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Are you a seasoned Data Engineer with expertise in ETL processes, database design, and performance tuning? We are seeking a Senior Data Engineer to join our clients team in Irving, TX, in a hybrid capacity. If you have a passion for creating efficient and robust database solutions and enjoy working both remotely and onsite, we'd love to hear from you.



Key Accountabilities

  • Design and Development: Lead the creation of scalable and reliable data pipelines for data ingestion, processing, storage, and retrieval.
  • Data Modeling: Develop and optimize data models and schemas for efficient storage, retrieval, and analytics, enhancing query performance and scalability.
  • Big Data Technologies: Utilize big data frameworks (e.g., Hadoop, Spark, Hive) to process and analyze large data volumes, supporting advanced analytics and machine learning initiatives
  • Infrastructure Management: Oversee and optimize data infrastructure, including cloud platforms, containerization technologies, and distributed computing environments.
  • Cross-Functional Collaboration: Partner with Data Science, Analytics, and Product teams to understand and address their data requirements.
  • Best Practices: Implement and advocate for best practices in data modeling, storage, and retrieval.
  • Data Security and Compliance: Ensure data security, privacy, and compliance with relevant regulations.
  • Documentation: Maintain comprehensive documentation for all data processes and systems.
  • Technology Evaluation: Assess new technologies and tools for data processing, storage, and retrieval, recommending improvements to enhance efficiency and scalability.
  • Continuous Improvement: Identify and lead opportunities for process improvement.
  • Mentorship: Guide team members to enhance their technical and leadership skills.


Education, Experience, & Skills Requirements:

  • Experience: 9-11 years in data engineering, with a focus on designing and building data pipelines.
  • Technical Proficiency: Expertise in data engineering technologies, including ETL frameworks, big data processing, SQL, and NoSQL databases.
  • Database Knowledge: Deep understanding of database systems, data modeling, and data warehousing.
  • Cloud Technologies: Experience with cloud-based data storage and processing technologies (e.g., AWS, Azure, Google Cloud).
  • Data Privacy and Governance: Knowledge of data privacy and governance policies.
  • Problem-Solving: Strong analytical and problem-solving skill
  • Collaboration: Ability to work effectively in a team environment.
  • Communication: Excellent communication and interpersonal skills.
  • Team Leadership: Experience in leading a team of data engineers and managing complex projects.
  • Agile Methodologies: Familiarity with agile software development methodologies.