Data Engineer

We are looking for an enthusiastic entry-level Data Engineer with a growing DevOps mindset to help build and maintain reliable scalable data pipelines that power business functions across the enterprise. This is a great opportunity for an early-career engineer to learn grow and build hands-on expertise youll support the team in developing data pipelines learn CI/CD and operational practices and take on increasing responsibility under the guidance of senior engineers.

Databricks Python (PySpark) SQL Data Pipelines CI/CD

• Help build and maintain data pipelines on Databricks under guidance.
• Develop ETL/ELT processes with attention to data quality consistency and scalability.
• Contribute to reusable frameworks for ingestion transformation and reconciliation across source systems.
• Follow established engineering standards coding standards pipeline patterns and ETL/ELT best practices.

• Assist with deploying changes through CI/CD and the Change Request (CR) lifecycle including validation and ticket closure.
• Participate in problem-solving and root-cause analysis learning to drive permanent fixes over recurring firefighting.
• Help monitor data workloads and support incident response with guidance from senior engineers.

• Work with Reporting Platform and Business teams to help deliver curated datasets for downstream consumers.
• Communicate progress and issues clearly to engineering peers and mentors.
• Document workflows and runbooks to support reproducibility and knowledge sharing.

• In your first 612 months youll build a solid understanding of the data platform confidently deliver assigned pipeline tasks and become comfortable with CI/CD and operational practices with support from senior engineers.

• Bachelors or Masters degree in Computer Science Information Technology or a related field.
• 1 years of experience (including internships) in data engineering or a related area fresh graduates with relevant internships are encouraged to apply.
• Foundational hands-on knowledge of Databricks Python (PySpark) and SQL for data processing.
• Exposure to building data pipelines (ETL/ELT) through projects internships or coursework.
• Basic understanding of CI/CD pipelines and Git-based version control.
• Familiarity with cloud platforms (AWS preferred) or willingness to learn.
• Awareness of monitoring and observability concepts.
• Good communication skills and eagerness to learn.

• Exposure to orchestration frameworks or streaming technologies.
• Basic familiarity with Infrastructure-as-Code and deployment tooling.
• Awareness of observability tooling for data platforms.
• Background or interest in semiconductor manufacturing or large-scale industrial data processing.
• Any Databricks or cloud certification is a plus.

• Eagerness to learn and grow data engineering skills.
• Ownership mindset takes pride in the quality of assigned work.
• Problem-solving orientation curiosity and attention to detail.
• Collaboration works well with peers and mentors across teams.
• Clear communication able to explain technical details to peers.

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