Senior Data Engineer

Cleo - Boston, MA

Full-time - Senior

Remote - Boston, MA

1,001-5,000 employees

Paper Manufacturing

About the position

The Senior Data Engineer at Cleo is a hands-on leadership role focused on designing, developing, and maintaining data pipelines and infrastructure. This position is crucial for setting the strategy for data systems, collaborating with cross-functional teams, and ensuring the scalability, reliability, and efficiency of data solutions, particularly for AI/ML applications. The role involves overseeing the creation of a data warehouse and ensuring data is transformed and optimized for machine learning and artificial intelligence.

Responsibilities

• Lead the Design and Build of Data Pipelines: Develop and maintain scalable, reliable, and efficient data pipelines that collect, process, and store large datasets.
• Set Data Infrastructure Strategy: Define and execute the strategy for building and maintaining data warehouses, data lakes, and other data storage systems that support both operational and analytical needs.
• Hands-On Data Transformation for AI/ML Models: Design and implement data transformation processes, including feature engineering, data preprocessing, and data augmentation.
• Build Data Structures and Metadata Management: Build and manage the data structures, metadata repositories, and related systems that support data transformation.
• Data Quality Controls and Risk Management: Establish and implement data quality controls to ensure data used in machine learning models is clean, consistent, and accurate.
• Collaborate with Cross-Functional Teams: Work closely with data scientists, ML engineers, product managers, and business leaders to understand data requirements.
• ETL Development and Optimization for AI/ML: Lead the development and optimization of ETL processes for ML/AI data.
• Optimize Data for Model Training and Inference: Ensure data pipelines are designed to support the needs of AI/ML model training.
• Data Governance for AI/ML: Define and implement data governance practices to ensure the secure, compliant, and ethical use of data in AI/ML workflows.
• Stay Current: Keep up with emerging trends in data engineering, particularly those related to AI/ML model development.

Requirements

• 5-7+ years of experience in data engineering, with a focus on transforming data for AI/ML models.
• Proven experience in hands-on data transformation and building data pipelines for AI/ML.
• Experience leading or mentoring data engineering teams.
• Strong experience with cloud platforms and big data technologies.

Benefits

• Competitive compensation
• Great Healthcare + Dental + Vision
• Flexible PTO
• Culture of support, encouraging Life-Work balance
• 401k match
• FSA and HSA options
• Employee Assistance Program
• Paid Parental Leave
• Accelerated title and salary growth potential
• A fun and energetic work environment.