Sales Data Engineer
At a glance
Mid-level Data Engineering role at onsemi. Petaling · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune ETL/ELT pipelines and DBT models that move sales data into reporting and analytics
- Write reusable SQL for transforming, combining and reporting data across Snowflake and SQL Server
- Investigate pipeline and database failures, find their root causes and put lasting fixes in place
- Use GitLab to manage code changes and deployments, working with teammates to uphold release standards
- Work with sales operations, BI, analytics and technical colleagues to turn data needs into scalable solutions
What you bring
- Four to seven years in data engineering, database development or a related discipline
- Hands-on work with Snowflake and Microsoft SQL Server, plus DBT for data modeling and transformation
- Experience building or supporting large-scale data pipelines and warehouse solutions
- Strong SQL skills and practical knowledge of ETL/ELT, data architecture and GitLab version control
Who this fits
This role suits a mid-level data engineer who can work independently, diagnose complex data problems and improve data quality, performance and automation. You’ll collaborate with sales operations, BI and analytics teams in a role based in Petaling, Malaysia.
From the employer
We are seeking a Data Engineer to support Sales Data and Analytics initiatives by designing, maintaining, and enhancing critical data pipelines and data flows. This role will be responsible for building scalable data solutions, troubleshooting and resolving data issues, improving existing Snowflake/SQL server data architectures, and ensuring reliable delivery of sales-related data across reporting and analytics platforms.
The ideal candidate will partner closely with Sales Operations, IT, and Analytics teams to identify data challenges, optimize data processes, and accelerate the resolution of sales data issues. By strengthening data quality, performance, and automation, this role will help create a more agile and reliable sales data ecosystem, reducing time to resolution for data issues/enhancements, and enabling the sales organization to access accurate, timely, and actionable information for decision making.
Data Engineering & Development
- Design, develop, maintain, and optimize data pipelines and ETL/ELT processes using modern data engineering practices.
- Build and maintain robust data models using DBT following best practices and standards.
- Develop high-quality, reusable, and efficient SQL code for data transformation, integration, and reporting requirements.
- Support data migration, integration, and modernization initiatives involving Snowflake and SQL Server platforms.
- Ensure data quality, consistency, reliability, and integrity across all data assets.
DevOps & Version Control
- Utilize GitLab for source control, code management, branching strategies, merge requests, and deployment processes.
- Collaborate with team members to maintain deployment standards and ensure solution quality.
Troubleshooting & Continuous Improvement
- Independently investigate, diagnose, and resolve complex data pipeline and database issues.
- Conduct root cause analysis and implement long-term solutions to prevent recurring problems.
- Proactively identify opportunities for automation, performance enhancement, and process optimization.
- Recommend innovative approaches, tools, and technologies to improve data platform efficiency and reliability.
Stakeholder Collaboration
- Work closely with sales ops, BI developers, business analysts, data analysts, and technical teams to understand requirements and deliver scalable solutions
Experience
- 4–7 years of experience in Data Engineering, Database Development, or related roles.
- Solid hands-on experience with different database technologies (Snowflake, Microsoft SQL Server).
- Proven experience using DBT for data transformation and modeling. Experience in designing and supporting enterprise-scale data pipelines and data warehouse solutions.
- Experience with GitLab and version control best practices.
- Mid to Expert-level SQL development skills with ability to write clean, efficient, and maintainable code.
- Solid understanding of ETL/ELT frameworks and modern data architecture.
Soft Skills
- Strong analytical and problem-solving skills.
- Ability to work independently with minimal supervision.
- Excellent troubleshooting and diagnostic capabilities.
- Proactive mindset with a focus on continuous improvement.
- Strong communication and stakeholder management skills.
- Ability to propose and drive innovative solutions that improve performance, scalability, and operational efficiency.
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