Data Engineer

MAGNETO & DIESEL INJECTOR SERVICE INC • Humble, TX

12d • Onsite

About The Position

As a Data Engineer, you will play a critical role in designing, building, and maintaining scalable data pipelines and architectures that support the organization's data analytics and business intelligence initiatives. You will be responsible for transforming raw data into reliable, accessible, and high-quality datasets that enable data scientists, analysts, and stakeholders to derive actionable insights. This role requires collaboration with cross-functional teams to understand data requirements and implement solutions that optimize data flow and storage. You will also ensure data integrity, security, and compliance with relevant standards while continuously improving data processing performance. Ultimately, your work will empower the organization to make data-driven decisions that drive business growth and innovation.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• Proven experience in data engineering or a similar role involving large-scale data processing.
• Strong proficiency in SQL and experience with relational databases.
• Hands-on experience with Apache Spark and Hive for big data processing.
• Proficiency in at least one programming language such as Python, Java, or Scala.
• Experience with data ingestion tools like Sqoop and scripting languages for automation.
• Build scalable data architecture for reporting, analytics, and AI initiatives.
• Develop ETL/ELT processes and data quality controls.
• Enable AI and machine learning capabilities with structured data foundations.
• Enable executive dashboards and operational KPI reporting.
• Support predictive analytics, automation, and business intelligence initiatives.
• Optimize database performance, data governance, and master data consistency.
• Partner with departments to create trusted and actionable data models.
• Performs other duties as assigned by supervisor.

Nice To Haves

• Master’s degree in a relevant technical field.
• Experience working in cloud environments such as AWS, Azure, or Google Cloud Platform.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Knowledge of data warehousing concepts and ETL best practices.
• Experience with real-time data processing frameworks and message queues.

Responsibilities

• Develop, construct, test, and maintain data architectures such as databases and large-scale processing systems.
• Design and implement data ingestion pipelines using tools like Apache Spark, Hive, and Sqoop to efficiently process structured and unstructured data.
• Write complex SQL queries and optimize them for performance to support data extraction and reporting needs.
• Collaborate with stakeholders to understand data requirements and deliver reliable datasets.
• Monitor and troubleshoot data pipeline issues, ensuring data quality, consistency, and security across systems.
• Automate repetitive data processing tasks using scripting languages and programming languages such as Python, R, Java, and Scala.
• Stay current with emerging data engineering technologies and best practices to continuously enhance data infrastructure.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level