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- Collaborate with cross-functional and global teams to comprehend business requirements and translate them into effective solutions.
- Design and manage resilient, scalable data models and architectures that cater to the evolving needs of the business, emphasizing efficiency, quality, and security.
- Implement data pipelines using tools such as Apache Airflow, AWS Glue, Redshift, S3, Python, and Informatica Cloud.
- Facilitate communication within and outside the project team to resolve conflicts related to implementation schedules, design complexities, and other challenges.
- Experience in Data Engineering leveraging AWS Redshift, S3, Glue, Airflow, Python, SQL and Kubernetes
- Familiarity with Informatica Cloud and Informatica Power Center is essential.
- Strong expertise in data modeling tools and methodologies, encompassing both structured and unstructured data environments.
- Demonstrated experience in data governance, data quality management, and data security practices.
- Exceptional analytical and problem-solving skills, enabling the translation of intricate technical challenges into actionable solutions.
- Ability to quickly learn and adapt to new technologies.
- Strong sense of ownership and growth mindset.
- Curiosity about the problem domain and an analytical approach.
- Strong influence skills to drive business adoption and change.
- Experience in data discovery of source systems like Oracle E-Business Suite and Salesforce is preferable.
- AWS
- Data Engineering
- SQL
- Python
- Informatica
Data Engineer - San Diego, United States - Spectraforce Technologies
Description
Position: Data EngineerLocation: Onsite (San Diego, CA)
Duration: 12 Months
Job description:
As a Data Engineer, you will play a pivotal role in shaping and implementing robust data architecture while constructing efficient data pipelines aligned with our organizational goals. This position supports various business functions, including Supply Chain, Finance, Sales & Marketing, and other corporate areas. The ideal candidate will possess a deep understanding of data architecture principles, data discovery/modeling, and the seamless integration of emerging technologies into a cohesive data ecosystem that fosters innovation, operational excellence, and strategic insights.
Principal Duties and Responsibilities:
Good to have qualifications