Data Engineer

Job Title - Data Engineer
Location: Remote
Duration: 6 Months

The Data Engineering team develops and supports scalable data platforms, pipelines, and automation solutions used across engineering organizations. This role focuses on building, maintaining, and optimizing production-grade data pipelines and data processing systems that improve data availability, quality, reliability, and engineering productivity.

The successful candidate will work closely with software, data, and engineering stakeholders to design and implement data solutions, troubleshoot production issues, integrate data from multiple sources, and improve the reliability and performance of existing data workflows. This is a hands-on individual contributor role focused on execution, delivery, and operational support.

Data Engineering & Pipeline Development

• Design, develop, test, and maintain scalable data pipelines and ETL/ELT workflows.
• Build data processing solutions using Python, SQL, and related technologies.
• Integrate data from multiple databases, APIs, files, and engineering systems.
• Develop reusable and maintainable data-processing frameworks and automation tools.
• Optimize data pipelines for performance, scalability, and reliability.

Database & Data Management

• Develop complex SQL queries, stored procedures, and data transformations.
• Work with relational databases and large-scale data systems.
• Perform data validation, cleansing, transformation, and quality checks.
• Troubleshoot database, query, and data-processing issues.
• Support data modeling and schema design as needed.

Production Support & Reliability

• Monitor production data pipelines, scheduled jobs, and data workflows.
• Troubleshoot failures across applications, databases, pipelines, and infrastructure.
• Improve logging, monitoring, alerting, and operational supportability.
• Identify root causes and implement long-term solutions to recurring issues.
• Maintain documentation and support knowledge-transfer activities.

Automation & AI-Assisted Engineering

• Develop automation to reduce manual data-processing and operational tasks.
• Use AI-assisted development tools to accelerate coding, testing, troubleshooting, and documentation.
• Maintain ownership of data accuracy, security, reliability, and production readiness.

Collaboration

• Partner with software engineers, data scientists, and engineering stakeholders to understand data requirements.
• Translate business and engineering requirements into practical data solutions.
• Participate in design reviews, code reviews, troubleshooting, and production-support activities.
• Communicate technical issues, project status, risks, and recommendations clearly.

• BS/MS in Computer Science, Data Engineering, Software Engineering, Electrical Engineering, or related field, or equivalent experience.
• Strong Python development skills.
• Strong SQL skills and experience with relational databases.
• Experience building and maintaining ETL/ELT or data-processing pipelines.
• Experience with production-quality software and data systems.
• Experience working with databases, APIs, and multiple data sources.
• Experience with Git or similar version-control systems.
• Strong debugging and problem-solving skills.
• Experience working in Linux/Unix environments.
• Strong written and verbal communication skills.

• Experience with Oracle, PostgreSQL, MySQL, or other enterprise databases.
• Experience with AWS, Azure, or other cloud platforms.
• Experience with Snowflake, Databricks, Spark, Kafka, Airflow, or similar data technologies.
• Experience developing REST API integrations.
• Experience with Docker and CI/CD tools such as Jenkins or GitHub Actions.
• Experience with data quality, observability, monitoring, and logging.
• Experience with distributed computing or batch-processing environments.
• Experience in semiconductor, hardware, manufacturing, or engineering environments.
• Experience using AI/LLM-assisted development tools.