Expert Data Specialist
Há 14 horas
As a seasoned data expert, you will design, develop and maintain data infrastructure that powers AI-driven insights across the organization. You will be responsible for building scalable data pipelines, operationalizing machine learning workflows and partnering closely with data scientists to bring models into production. This role is ideal for someone who loves leveraging their technical expertise in Python to drive business outcomes. Your skills in data modeling, data warehousing and distributed systems will be highly valued in this position. The successful candidate will have experience working with Snowflake as a central data warehouse, including data models and pipelines that run through it. They will also have hands-on experience with cloud platforms such as AWS, GCP or Azure, as well as data orchestration tools like Airflow, Prefect or Dagster. A strong understanding of MLOps best practices, including versioning, CI/CD for ML and automated retraining workflows, is essential for this role. The candidate should also be familiar with feature engineering, inference pipelines and deploying models. Key Responsibilities Build, optimize and maintain ETL/ELT pipelines using Python and modern data engineering frameworks. Architect and manage data workflows, ensuring accuracy, scalability and reliability. Work closely with data scientists to deploy, monitor and tune machine learning models. Develop feature engineering pipelines, preprocessing workflows and model-serving APIs. Integrate data from various sources, including APIs, databases, cloud storage and streaming platforms. Required Skills & Experience 3-7+ years of experience as a Data Engineer, Python Engineer or similar backend/data role. Strong proficiency in Python, including building production-grade data pipelines. Experience with Snowflake, including data modeling, Snowpipe, tasks, streams, stored procedures and performance optimization. Experience with AI/ML workflows, feature engineering, inference pipelines or deploying models. Proficiency in SQL and relational databases, including PostgreSQL, MySQL and SQL Server. Hands-on experience with at least one cloud platform, including AWS, GCP or Azure. Preferred Qualifications Experience with Spark, Databricks or other big-data processing tools. Experience ingesting and transforming data at scale on Snowflake, including optimization of virtual warehouses. Familiarity with Kafka, Kinesis or other streaming platforms. Understanding of CI/CD pipelines, including GitHub Actions, GitLab CI and Jenkins.
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