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Experience Level
Mid to Senior
Qualifications
Proven experience as a Data Engineer or in a similar role. Strong proficiency in SQL and data modeling. Experience with data warehousing solutions and ETL processes. Familiarity with cloud platforms (AWS, Azure, GCP) is a plus. Ability to work collaboratively in a team environment. Excellent problem-solving skills and attention to detail.
About the job
blend360 is hiring a Senior Data Engineer in Montevideo. This position focuses on building and maintaining data solutions that support business insights and decision-making. The Senior Data Engineer will work closely with teams across the company to ensure data infrastructure supports blend360’s strategic objectives.
What You Will Do
Design and implement data architectures that meet business needs
Maintain and optimize data systems for reliability and performance
Collaborate with colleagues from different departments to align data infrastructure with company goals
Support the use of data assets to drive analytics and decision-making
What We Look For
Strong experience in data engineering and architecture
Ability to create and maintain scalable data solutions
Comfort working with cross-functional teams
Interest in supporting business growth through effective data use
Location
This role is based in Montevideo.
About blend360
blend360 is a leader in data-driven solutions, dedicated to helping organizations harness the power of their data. Our team of experts provides innovative strategies and technologies that transform data into actionable insights. Join us and be part of a company that values creativity, collaboration, and continuous improvement.
At SunnyData, we are dedicated to guiding our clients through their data journey to empower their business operations. We understand that a robust data infrastructure is essential for achieving exceptional data-driven outcomes, including scalable architectures, resilient data engineering pipelines, straightforward data consumption layers, and precise machine…
At SunnyData, we are dedicated to empowering our clients by constructing highly scalable architectures, developing robust data engineering pipelines, and creating user-friendly data consumption layers. Most importantly, we focus on building advanced Machine Learning (ML) and Artificial Intelligence (AI) applications that drive exceptional business outcomes. As a Senior Machine Learning Engineer, you will spearhead intricate data projects, design predictive models, and implement scalable machine learning solutions. You will collaborate across various teams including engineering, product, and analytics to generate actionable insights and impact critical business decisions.Your ContributionLead the architecture, development, and deployment of machine learning models.Work with extensive and intricate datasets to extract valuable insights and establish predictive analytics pipelines.Partner with data engineers to design and enhance cloud-based data solutions.Convert business challenges into data-driven strategies utilizing statistical modeling and machine learning methodologies.Streamline data workflows and model deployment processes using cloud services and CI/CD methodologies.Guide junior data scientists and contribute to the establishment of best practices in model development and implementation.Effectively communicate insights and strategic recommendations to stakeholders and executive leadership.Desired QualificationsA minimum of 5 years of experience in data science or machine learning positions.Strong proficiency in Python (including libraries such as pandas, scikit-learn, PyTorch, or TensorFlow) and SQL.A solid foundation in statistics, A/B testing, and machine learning algorithms.Proven experience in building and deploying models in production settings.Familiar with MLOps tools and practices (e.g., MLflow, SageMaker Pipelines, Airflow).Exceptional communication and leadership capabilities.Preferred QualificationsExperience with big data technologies (e.g., Spark, EMR).Familiarity with containerization technologies (e.g., Docker, ECS, EKS) and serverless architectures.EducationBachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field is preferred.
Are you eager to elevate your career in the dynamic and cutting-edge field of data engineering?At SunnyData, we are dedicated to guiding our clients through their data journey, empowering their businesses with actionable insights. We understand that a robust foundation is essential for achieving exceptional data-driven outcomes: from highly scalable architectures and resilient data engineering pipelines to intuitive data consumption layers and precise machine learning and AI applications. As a Data Engineer, you will be instrumental in this journey. Collaborating with both internal teams and clients, you will design, construct, and deploy data solutions that capture, analyze, transform, and leverage data to enhance Artificial Intelligence, Machine Learning, and Business Intelligence initiatives.Your ImpactContribute to a team that supports both new and existing clients with their data engineering requirements.Advise clients on optimal technical strategies to achieve their objectives.Manage multiple customer accounts, tracking and reporting on their progress.Design, develop, and operationalize intricate data solutions, troubleshoot issues, implement transformations, and suggest data cleansing and quality strategies.Evaluate data sources to ascertain their value and recommend inclusion in analytical workflows.Apply core data management principles, including data governance, security, and quality.Collaborate with teams to deliver solutions and educate end users on data products and analytic environments.Conduct data and system analysis, addressing defects and incidents of moderate complexity and implementing corrections as necessary.Test data movement, transformation code, and data components.QualificationsSelf-motivated individual with a commitment to continuous learning and excellent time management skills.Strong verbal and written communication skills in English.Availability for either part-time (6 hours) or full-time (8 hours) work.Familiarity with public cloud services such as AWS, Azure, or GCP.Preferred: Experience with one or more data engineering technologies (e.g., Spark, Hadoop, Kafka).
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