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.