What You ll Be Doing:
- Building the data engineering and analytics infrastructure for our new Enterprise Data Platform using Snowflake and Fivetran.
- Leading the development of data models, algorithms, data pipelines, and insights to enable data-driven decision-making.
- Collaborating with team members to shape the design and direction of the data platform.
- Working end-to-end on data products, from problem understanding to developing data pipelines, dimensional data models, and visualizations.
- Providing support and advice to business users, including data preparation for predictive and prescriptive modeling.
- Ensuring consistency of processes and championing best practices in data management.
- Evaluating and recommending new data tools or processes.
- Designing, developing, and deploying scalable AI/Generative AI and machine learning models as needed.
- Providing day-to-day production support to internal business unit customers, implementing enhancements and resolving defects.
- Maintaining awareness of emerging trends in AI, Generative AI, and machine learning to enhance existing systems and develop innovative solutions.
The Impact You Will Have:
- Driving the development of a cutting-edge data platform that supports enterprise-wide data initiatives.
- Enabling data-driven decision-making across the organization through robust data models and insights.
- Enhancing the efficiency and effectiveness of data management processes.
- Supporting business users in leveraging data for predictive and prescriptive analytics.
- Innovating and integrating advanced AI and machine learning solutions to solve complex business challenges.
- Contributing to the overall success of Synopsys by ensuring high-quality data infrastructure and analytics capabilities.
What You ll Need:
- BS with 5+ years of relevant experience or MS with 3+ years of relevant experience in Computer Sciences, Mathematics, Engineering, or MIS.
- 5 years of experience in DW/BI development, reporting, and analytics roles, working with business and key stakeholders.
- Advanced knowledge of Data Warehousing, SQL, ETL/ELT, dimensional modeling, and databases (e.g., mySQL, Postgres, HANA).
- Hands-on experience with modern data stack tools, including cloud data warehouses (Snowflake), transformation tools (dbt), and cloud providers (Azure, AWS).
- Experience with data ingestion tools (e.g., Fivetran, HVR, Airbyte), CI/CD (GitLab, Kubernetes, Airflow), and data catalog tools (e.g., Datahub, Atlan) is a plus.
- Proficiency in scripting languages like Python, Unix, SQL, Scala, and Java for data extraction and exploration.
- Experience with visualization tools like Tableau and PowerBI is a plus.
- Knowledge of machine learning frameworks and libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch) and LLM models is a plus.
- Understanding of data governance, data integrity, and data quality best practices.
- Experience with agile development methodologies and change control processes.
