Data Engineer
hace 2 semanas
**Descripción**:
**Data Engineer**
**Responsibilities**:
- Facilitator of data storage, assisting the integration, summarization, and transformation of data to make it easier to analyze for business intelligence.
- Creating, designing and developing data models.
- Work with product and engineering teams to understand requirements, evaluate new features and architecture to help drive decisions.
- Perform detailed analysis of business problems and technical environments and use this in designing quality technical solution.
- Design and implement innovative analytical solution using Hadoop, NoSQL, and other Big Data related technologies, evaluating new features and architecture in Cloud/ on premise/ Hybrid solutions.
- Create and populate data lakes and a data warehouse to facilitate data analysis and data science projects.
- Prepare plans for all ETL (Extract/Transformation/Load) procedures and architectures.
- Evaluate and implement dynamic, interactive, and static visualizations of data.
- Actively participate in code review and test solutions to ensure it meets best practice specifications.
- Write project documentation.
**Skills**:
- 3+ Experience involved in data Integration projects, data lakes and warehousing design, implementing, managing and monitoring.
- 3+ Experience with multidimensional analysis, cubes, OLAP, denormalization, definition of dimensions, measures, fact tables, etc.
- 3+ Experience using data warehouse management services ( Azure Synapse Analytics, AWS Redshift or Big Query).
- 3+ Experience with data ingestion, data streaming and streams processing services (Stream Analytics, Data Lake Store, Event Hubs, Kinesis Data Streams).
- 3+ Experience with platforms and tools for creating ETL jobs and orchestration of data workflows services (Data Factory, Data Catalog, Data Pipeline, AWS Glue or Cloud Composer).
- 3+ Experience with the Azure data ecosystem (Blob Storage, Data Catalog, Azure Data Lake, Functions, Azure Queue Storage, AVM, SQL Database, Databricks, Virtual Network, AKS, etc).
- 3+ Experience with secure cloud data lakes, considering aspects such as Isolation, platform hardening, network perimeter, host security, authorization, encryption, vulnerability management, compliance & incident response, data loss prevention, etc.
- 2+ Experience using Big Data tools (Hive, Hadoop, EMR, Spark, etc).
- 2+ Experience with Python and data-related libraries (e.g., pandas, numpy).
- Strong experience in SQL, NoSQL databases and data structure algorithms (Sort, Search, List, etc).
- Strong experience using source control management and CI/CD.
**Nice to have Microsoft Certified: Data Analyst Associate (DA-100), AWS Certified Data Analytics - Specialty (DAS-C01) or equivalent.**
**Requisitos**:
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