Senior Data Engineer
Há 7 dias
We are seeking a talented and experienced Senior Data Engineer. As part of our diverse practices, including Data, Machine Learning, DevOps, Application Development, and QA, you will collaborate with a multidisciplinary team of data engineers, machine learning engineers, and application developers. You will encounter numerous technical challenges and have the opportunity to contribute to exciting open-source projects, build internal solutions, and engage in R&D activities, providing an excellent environment for professional growth.
Let's work together to build a better future for everyone Requirements:
- 5+ years of hands-on experience in data engineering, with a strong emphasis on Databricks and Apache Spark.
- Expertise in cloud platforms (AWS preferred, GCP, or Azure) preferably with relevant certifications.
- Proficiency with cloud data warehouse technologies (Snowflake/Redshift/Clickhouse).
- Proven experience in handling batch data workflows using Airflow or similar tools.
- Experience in handling real-time data using Kafka and streaming processing frameworks.
- Strong command of Python and SQL for building scalable and efficient data pipelines.
- Strong communication skills with the ability to collaborate effectively in English.
- Exceptional problem-solving skills and the ability to thrive in fast-paced environments.
- Solid experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation.
- Databricks Data Engineering certification.
- Experience designing scalable APIs using frameworks such as FastAPI or Flask.
- Familiarity with BI tools such as Power BI, QuickSight, Looker, or Tableau.
- Experience in implementing Data Mesh architecture or distributed data solutions.
- In-depth knowledge of Data Governance principles, including Data Quality, Lineage, Security, and Cost Optimization.
- Familiarity with Machine Learning frameworks (e.g., AWS SageMaker, MLflow) and classical ML tasks (e.g., OCR).
- Experience in building Generative AI applications such as chatbots and RAG systems.
- Collaborate with clients to understand their IT environments, applications, business requirements, and digital transformation objectives.
- Collect, process, and manage large volumes of structured and unstructured data from diverse sources.
- Work directly with Data Scientists and ML Engineers to design and maintain robust, resilient data pipelines that power Data Products.
- Define and develop data models that unify disparate data across the organization.
- Design, implement, and optimize ETL/ELT pipelines, ensuring scalability, performance, and maintainability.
- Leverage Databricks and Apache Spark to perform complex data transformations and processing.
- Build, test, and deploy scalable data-driven solutions in collaboration with cross-functional teams.
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