Senior Data Engineer

Senior Data EngineernRemote - USnCleo is a cloud integration technology company focused on business outcomes. Every day, we ensure that each one of our 4,000+ customers' potential is realized by delivering solutions that make it easy to discover and create value through the connections and integration of enterprise applications supporting critical workflows. By providing the industry’s most complete and flexible integration offerings, we are helping our clients build trusted relationships across their partner ecosystems today, while providing all the control and visibility they need to advance their business tomorrow. In a nutshell, Cleo is a rapidly growing category leader in ecosystem integration software and we have experienced tremendous growth over recent years.nThe Senior Data Engineer is a hands-on leader responsible for designing, developing, and maintaining data pipelines and infrastructure at Cleo. This role involves setting the strategy for data systems, collaborating closely with cross-functional teams, and ensuring the scalability, reliability, and efficiency of data solutions. The Senior Data Engineer will focus on data infrastructure needs for AI/ML models , overseeing the creation of a data warehouse and associated systems from scratch, and ensuring data is properly transformed and optimized for machine learning and artificial intelligence applications. This role is integral to building the processes that support data transformation , data structures , metadata management , data quality controls , and workload management .nWhat You Will Be DoingnnnLead the Design and Build of Data Pipelines : Develop and maintain scalable, reliable, and efficient data pipelines that collect, process, and store large datasets. Ensure these systems are optimized for AI/ML model training and inference.n nnSet 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. Ensure systems are optimized for AI/ML model workflows.n nnHands-On Data Transformation for AI/ML Models : Design and implement data transformation processes, including feature engineering , data preprocessing , and data augmentation , to ensure data is in the right format for machine learning models.n nnBuild Data Structures and Metadata Management : Build and manage the data structures, metadata repositories, and related systems that support data transformation, ensuring the organization has well-documented, accurate, and accessible data for AI/ML workflows.n nnData Quality Controls and Risk Management : Establish and implement data quality controls to ensure that data used in machine learning models is clean, consistent, and accurate. Identify and raise risks at all stages of the data engineering process, including data ingestion, transformation, and storage.n nnCollaborate with Cross-Functional Teams : Work closely with data scientists , ML engineers , product managers , and business leaders to understand data requirements and ensure data systems meet the needs of AI/ML initiatives. Provide hands-on leadership to guide teams in transforming data for model training.n nnETL Development and Optimization for AI/ML : Lead the development and optimization of ETL (Extract, Transform, Load) processes for ML/AI data. Focus on efficiently moving and transforming large datasets, ensuring data quality and readiness for model training and deployment.n nnOptimize Data for Model Training and Inference : Ensure data pipelines are designed to support the needs of AI/ML model training, such as handling large volumes of data, managing data quality, and enabling fast model iteration.n nnData Governance for AI/ML : Define and implement data governance practices to ensure the secure, compliant, and ethical use of data in AI/ML workflows.n nnStay Current : Keep up with emerging trends in data engineering, particularly those related to AI/ML model development, and implement best practices to optimize data systems for machine learning.n n nYour QualificationsnnnExperience : 5-7+ years of experience in data engineering, with a focus on transforming data for AI/ML models and optimizing data systems to support machine learning and artificial intelligence workflows.n nnHands-On Expertise : Proven experience in hands-on data transformation and building data pipelines for AI/ML, including data preprocessing, feature engineering, and model-specific data handling.n nnLeadership : Experience leading or mentoring data engineering teams, providing hands-on guidance for AI/ML-related projects and collaborating with cross-functional teams.n nnCloud and Big Data : Strong experience with cloud platforms and big data technologies , particularly in the context of AI/ML model development .n n nA few things we have to offer:nnnCompetitive compensationn nnGreat Healthcare + Dental + Visionn nnFlexible PTOn nnCulture of support, encouraging Life-Work balancen nn401k matchn nnFSA and HSA optionsn nnEmployee Assistance Programn nnPaid Parental Leaven nnRepresenting a company with 4,000+ clients and a 99% retention raten nnAccelerated title and salary growth potentialn nnA fun and energetic work environment that makes you excited to go to work every dayn n nCleo Communications, LLC is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status or any other characteristic protected by law.