Staff Analytics Engineer

Key Responsibilities:

• End-to-End Implementation: Take ownership of the entire analytics lifecycle, from requirements gathering and data pipeline development to delivering actionable insights and dashboards.
• Data Pipeline Development: Design, develop, and maintain robust ETL/ELT pipelines to process and transform data from various sources into usable formats.
• Data Modeling: Create and maintain optimized data models to support analytics and reporting needs, ensuring data integrity and consistency.
• Understanding Business Processes: Develop a deep understanding of business processes, particularly within supply chain sites, to identify opportunities for improvement and enable tracking of key performance indicators (KPIs) such as Safety, Quality, Delivery, Inventory, and Productivity (SQDIP).
• Collaboration with Business Users: Partner closely with business users to understand their data needs, translate requirements into technical solutions, and ensure analytics solutions align with business goals.
• Data Quality Assurance: Implement data validation and monitoring processes to ensure high-quality and reliable data for analytics.
• Performance Optimization: Optimize data workflows and queries for efficiency and scalability, ensuring minimal latency and maximum performance.
• Analytics and Visualization: Develop and maintain interactive dashboards and visualizations using Spotfire to enable data-driven decision-making across the organization.
• Ownership and Accountability: Act as the primary owner of analytics solutions, ensuring timely delivery, ongoing maintenance, and continuous improvement of data products.
• Documentation and Standards: Develop and maintain documentation for data pipelines, models, and processes, ensuring adherence to best practices and company standards.
• Continuous Improvement: Identify opportunities for process improvement and automation within data workflows and analytics operations.
• Compliance and Security: Ensure data solutions comply with organizational policies, data privacy regulations, and security standards.

Minimum Qualifications:

• Bachelor’s degree from accredited university or college with minimum of 4 years of professional experience OR Associates degree with minimum of 7 years of professional experience OR High School Diploma with minimum of 9 years of professional experience
• Minimum 4 years of professional experience in data and Analytics
• Note: Military experience is equivalent to professional experience

Eligibility Requirements:

• Legal authorization to work in the U.S. is required.  We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Preferred Qualifications:

• Proven experience with SQL, Python, and data visualization tools (e.g., Spotfire).
• Familiarity with cloud platforms (e.g., AWS, Azure) and data warehousing solutions (e.g., Snowflake, Redshift).
• Strong understanding of data modelling, ETL/ELT processes, and database design.
• Proficiency in data pipeline tools (e.g., Apache Airflow, dbt, or similar).
• Knowledge of data governance, security, and compliance best practices.
• Excellent problem-solving and analytical skills.
• Effective communication and collaboration skills to work with business users and cross-functional teams.

Desired Qualifications:

• Experience with machine learning workflows and tools.
• Familiarity with Agile methodologies and tools like JIRA.
• Knowledge of GE Aerospace’s FLIGHT DECK operating system and lean principles.
• Experience in the aerospace or manufacturing industry

This role requires access to U.S. export-controlled information. Therefore, employment will be contingent upon the ability to prove that you meet the status of a U.S. Person as one of the following: U.S. lawful permanent resident, U.S. Citizen, have been granted asylee or refugee status (i.e., a protected individual under the Immigration and Naturalization Act, 8 U.S.C. 1324b(a)(3)).