Data Engineer

The Data Engineer role focuses on data collection, quality, governance, and enabling machine learning, while leading efforts to design, build, and maintain secure, scalable data platforms that support data-driven decision making across the organization.

Responsibilities

• Oversees one or more project teams of data engineers through all stages of design and development for complex, secure, and high-performance data solutions and models, including design, analysis, coding, testing, and integration of structured and unstructured data.
• Evaluates designs and project activities for compliance with architecture, security, and quality guidelines and standards; delivers concrete feedback to elevate product quality and mitigate failure risk.
• Provides domain-specific expertise and leadership for data systems across cross-organization projects, programs, and activities.
• Champions innovation by integrating new technologies within big data initiatives.
• Collaborates and communicates with project teams regarding progress and issue resolution.
• Represents the data engineering team across large and more complex development projects.
• Supports coaching and training of business analytics solution users to enhance decision-making capabilities.
• Maintains a high level of data integrity by using tools to monitor and bulk update data changes.
• Cultivates and manages relationships across the organization.
• Provides guidance and mentoring to less experienced staff members.

Requirements

• Bachelor's or graduate degree in Computer Science, Information Technology, Software Engineering, Statistics/Mathematics, or related discipline, or an equivalent combination of work experience or demonstrated competence.
• Typically 7-10 years of relevant experience in data analytics, data engineering, data modeling, or related field.
• Certification in programming languages such as SQL, Python, or similar.
• Experience with Agile methodologies.
• Proficiency with Amazon Web Services (AWS), Apache Hadoop, Apache Kafka, and Apache Spark.
• Familiarity with big data concepts, data warehousing, data pipelines, and ETL processes.
• Experience with Java, Python, or Scala; strong SQL skills.
• Knowledge of machine learning concepts and applications.
• Proficiency with Microsoft Azure.
• Demonstrated ability to design scalable data solutions and lead cross-functional initiatives.
• Strong communication, results orientation, learning agility, digital fluency, and customer centricity.
• Demonstrated ability to build cross-team collaboration and mentor staff.

Technologies

• Amazon Web Services
• Apache Hadoop
• Apache Kafka
• Apache Spark
• Microsoft Azure
• Python
• Java
• Scala
• SQL

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Long term and short term disability insurance
• Employee assistance program
• Flexible spending account
• Life insurance
• Generous paid parental leave based on tenure (4-12 weeks)
• 11 paid holidays
• Additional flexible paid vacation and sick leave

Salary

• USD 130,700 - 205,200 per year

Job Details

• Location: Spring, TX (onsite)
• Type: Full-time
• Schedule: Full time
• Shift: No shift premium (United States of America)