Who You Are
You are a detail-oriented and technically proficient Data Engineer looking for an opportunity to become the cornerstone of Lugano’s data infrastructure. You are excited to leverage your expertise in data analysis, software engineering, and statistical modeling to play a pivotal role in transforming raw data into strategic insights that propel the business forward.
In this newly created role due to growth, you will be reporting directly to the Vice President of technology, and collaborating with diverse teams across multiple departments to innovate and implement solutions that streamline operations and boost performance. In addition, your precision, strong business acumen, and effective communication skills will be key to your success in this growth-fueled opportunity where you will have a direct impact in shaping the future of data at Lugano.
Does this sound like you? If so, apply today, and let’s be remarkable together!
What You Will Do
- Design, develop, and maintain scalable data pipelines and workflows for processing and analyzing large-scale datasets.
- Perform complex data analysis to identify trends, patterns, and actionable insights.
- Build and optimize data models, algorithms, and machine learning models to support business objectives and uncover valuable business insights.
- Implement data-driven solutions for data extraction, transformation, and loading (ETL) processes.
- Develop and deploy data visualizations and reports to communicate and report findings to a wide variety of stakeholders and systems.
- Collaborate with departments across the organization to understand data requirements and deliver data solutions that support business goals and objectives.
- Ensure impeccable data quality and integrity through rigorous testing and validation.
- Stay current with industry trends and best practices in all things data engineering and analytics.
What You Will Bring
- Professional experience and proven success as a Data Engineer, or similar role, within a dynamic, fast-paced, high-growth organization.
- Expert-level proficiency in SQL and relational databases.
- Deep skills and experience with data warehousing, ETL frameworks, and Azure Data Analytics technology (Synapse, Data Lake, Azure Pipeline, Databricks, etc.)
- Experience with data visualization tools (e.g., Power BI) and statistical analysis tools.
- Solid understanding of machine learning techniques and algorithms is an advantage.
- Ability to translate complex analytical findings into clear and actionable insights.
- Possession of an analytical mindset and adept problem-solving skills, enabling effective identification and resolution of complex issues.
- Excellent organizational skills, enabling efficient management of tasks, priorities, and deadlines within a dynamic testing environment.
- Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, or a related field.
Pay Transparency
Targeted base compensation is $140,000 per year, plus annual bonus. The total compensation package is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Our Work Environment
Our workplace is clean, orderly, appropriately lighted and ventilated with the proper safety compliance. Noise levels are considered low and daily physical activities are considered light: office work, seldom lifting up to 25 pounds, bending, stooping, kneeling, or walking. Employees must have the stamina to work long hours if assigned. Hours and days of work may vary by position. Reasonable accommodation may be made to allow people with disabilities to perform the essential functions of their job within the environment.
![Lugano Diamonds](https://s7-recruiting.cdn.greenhouse.io/external_greenhouse_job_boards/logos/400/245/900/resized/Lugano_logo_sq.jpg?1699576494)
Lugano Diamonds
A luxury retail company committed to creating a diverse work environment and offering employees a generous compensation package with commission and bonus plans, multi-option healthcare plans, 401k with match, and paid time off
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