Vagas: data engineer - Rio Grande do Sul

Who we are?

Inbenta is a global technology company headquartered in Allen, Texas with offices and team members around the world, the curent position is for the Brazil office. We develop an Automatic Language Processing (or Natural Language Processing – NLP) engine, which provides answers to human intentions formulated in natural language. Based on our proprietary and patented technology, Inbenta builds a set of conversational solutions for businesses such as chatbots, knowledge management tools, digital demos, and search engines. Our customers include many global blue-chip companies in Banking, Insurance, Automotive, Services, Retail, Transportation, and other sectors.

What are we looking for?

The Data Engineer plays a pivotal role in harnessing the power of a unified data and analytics platform built on AWS and Snowflake to deliver consistent, high-value business insights. This role encompasses implementing domain-driven designs for data models, APIs, and products, as well as collecting, translating, and validating data for analysis. The ideal candidate is naturally curious, thrives in a fast-paced, dynamic environment, and excels at collaborating with global team members.

Responsibilities

• Develops enterprise solutions related to operational data stores, data warehouses, analytics, and business intelligence

• Designs and develops Data Models, Data Pipelines, Data Warehouses, Data Lakes, ETL/ELT processes

• Executes modern data engineering principals and data modernization practices

• Provides expertise across the Data & Analytics domain including data storage (Data Lake & Data Warehouse), data integration, business intelligence, artificial intelligence & machine learning

• Prepares technical design specifications and other documentation

• Ensures data is secure and compliant under regulations

• Continuously improves efficiency, accuracy, and effectiveness of the data

Requirements

Education, Experience & Minimum Requirements

• Bachelor’s degree in computer science, data science, or relevant field.

• Required Fluency in English (both written and spoken)

• A minimum of 6 years of designing, building, and managing modern enterprise data.

• Sas based Tech, Banking, insurance, or other similar financial services experience strongly preferred.

Technical Competencies

• AWS, Google or Azure (SQL, Data Factory, Data Hub, etc.)

• Containerization (i.e., Kubernetes)

• Graphite, Splunk, Kafka, Snowflake

• API management/gateway, JSON, Python, Query tuning

• Excellent knowledge of best practices, industry trends and compliance requirements in Data Modeling, Governance and Data Management

• Strong knowledge of data profiling, Data standardization, transformation, Data cleansing

• Strong experience building big data solutions using Data Lake, Data Warehouse, Data Products

• Expert level understanding of different data storage technologies, and appropriate use cases for each – Relational, NoSQL, Time-Series, Graph, etc.

• Expert level understanding of data-integration technologies – ETL/ELT, Streaming, Replication, etc.

Functional Competencies

• Excellent interpersonal, written, and verbal skills

• Strong strategic mindset in connecting business drivers and a foundational understanding of company data in support of data driven approaches to analytics and insights

• Strong attention to detail