- Collaborate with business stakeholders to understand data requirements and translate them into technical solutions for data driven transformations.
- Design, architect, and implement data pipelines using cloud platforms/tools (Snowflake, AWS, ,Databricks, Airflow, Power BI etc.)
- Develop and maintain scalable data models that support business processes and analytical needs.
- Ensure data quality, integrity, and security across all data solutions.
- Implement and optimize Spark processing for efficient data transformations and analytics.
- Evaluate and recommend new technologies and tools to enhance data architecture and analytics capabilities.
- Work closely with data scientists to support advanced analytics and machine learning initiatives.
- Lead efforts in data governance and compliance, ensuring adherence to industry standards and regulations.
- Mentor and guide junior team members in best practices for data architecture and engineering.
What Were Looking For
Required Skills and Qualifications:
- Bachelor s degree in computer science, Information Systems, or a related field; master s degree preferred.
- Proven experience (7+ years) as a Data Architect, Data Engineer, or similar role in a complex IT environment.
- Strong proficiency with cloud data platforms such as Snowflake/AWS, along with analytics tools such as Microsoft Power BI.
- Experience with data ingestion from diverse sources including Oracle ERP, SFDC, Workday, ServiceNow, etc.
- Strong proficiency in Python for data engineering
- Hands-on expertise in data modeling, schema design, and performance tuning for large-scale data systems.
- Proficiency in Spark, Airflow, and other data processing and orchestration tools.
- Knowledge of data security best practices and compliance requirements (GDPR, CCPA, etc.).
- Excellent communication skills with the ability to collaborate effectively with cross-functional teams and business stakeholders.
- Strong analytical and problem-solving skills, with a keen attention to detail.
Preferred Qualifications:
- Certification in cloud platforms (Snowflake/AWS/Azure/Power BI) and/or other data engineering tools or technologies.
- Experience with AWS or Databricks platforms for data science and advanced analytics.
- Familiarity with semiconductor industry-specific data challenges and requirements especially supply chain and product costing.
