Data Engineer (Python)

1. Position Summary

We are looking for a Data Engineer to join our team and contribute to a major project within the semiconductor manufacturing domain. The role involves designing and implementing data pipelines, managing Oracle-based data environments, and supporting end-to-end BI processes — from data ingestion to visualization. This position is based on-site at our partner’s advanced manufacturing facility, offering hands-on exposure to large-scale industrial data systems.

2. Key Responsibilities

• Design, develop, and maintain Python-based applications and APIs to extract, transform, and deliver data in JSON format.
• Design and create robust data models to support efficient querying and reporting.
• Define relationships, hierarchies, and calculated columns/measures that align with business logic.
• Design, develop, and maintain data pipelines and ETL workflows for manufacturing data (ERP, MES, SPC, FDC, etc.).
• Implement and optimize database logic, including stored procedures, functions, and PL/SQL scripts.
• Build and manage staging schemas, data validation processes, and data transformation logic.
• Develop and maintain data marts and dimensional models to support analytics and reporting.
• Collaborate with BI developers and analysts to deliver Power BI dashboards, KPI reports, and visual analytics.
• Ensure data accuracy, consistency, and completeness across multiple source systems.
• Support data governance, documentation, and performance tuning efforts.
• Partner with internal and external stakeholders to ensure timely and high-quality data delivery for business use.
• Perform any ad-hoc duties assigned by the Company as and when required.

3. Qualifications& Skills

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Minimum 3 years of experience in data engineering, data integration, or BI development.
• Proficient in Python programming, specifically for data extraction, API development, and JSON data manipulation.
• Strong understanding of data warehousing concepts, schema design, and ETL best practices.
• Solid working experience with relational databases (e.g. Oracle, SQL Server, MySQL, PostgreSQL), including stored procedures and query optimization.
• Proficient with ETL tools such as Pentaho Kettle, Informatica, Talend, or similar.
• Experience developing reports and dashboards in Power BI (or Tableau/Qlik).
• Familiarity with SQL pipelines, data validation, and data replication tools.
• Strong analytical and problem-solving mindset with attention to data quality and performance.
• Ability to work collaboratively with business, IT, and engineering teams in fast-paced environments.
• Excellent documentation and communication skills.

4. Preferred /Additional

• Experience in semiconductor or manufacturing systems (ERP, MES, SPC, FDC) preferred.
• Exposure to data replication frameworks (Oracle Golden Gate, SharePlex, AWS Glue) is an advantage.
• Experience developing custom Python applications/APIs for data extraction and familiarity with JSON data structures is highly preferred.
• Familiarity with cloud-based data warehouses (Snowflake, Redshift, Synapse) and Giga Report is a plus
• Knowledge of data governance frameworks, metadata management, and data security best practices.