Senior Data Engineer

SysMap Solutions

. Design, develop, and maintain data infrastructure and architecture for the Legal department’s Artificial Intelligence initiatives .

Posted 11/4/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering and solution architecture, with a strong focus on developing and maintaining scalable data pipelines and architectures. Proficient in SQL, Python, and ETL/ELT processes, while ensuring compliance with data governance and protection regulations.

Highest-signal resume keywords

Data EngineeringSQL ProficiencyETL/ELT Pipeline DevelopmentLakehouse Architecture KnowledgeApache Spark Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Infrastructure DesignData Pipeline DevelopmentData TransformationData Quality MonitoringData ModelingDocument ProcessingMachine Learning PreparationData GovernanceData LakesData Warehouses

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

Apache AirflowPySparkCloud-Based Data PlatformsDataOpsCI/CD Practices

Industry Keywords

Legal DataLGPD ComplianceGenerative Artificial IntelligenceLarge Language ModelsRetrieval-Augmented GenerationVector Databases

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudETLPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design, develop, and maintain data infrastructure and architecture for the Legal department’s Artificial Intelligence initiatives
Design, develop, and maintain robust, scalable, and efficient data pipelines
Ingest, extract, transform, cleanse, standardize, and enrich large volumes of data
Structure and implement Lakehouse and Medallion architectures (Bronze, Silver, and Gold)
Transform raw data into structured and reliable data products, with a focus on the Gold layer
Prepare and make data available for Artificial Intelligence, Machine Learning, and LLM solutions
Develop ETL/ELT processes for integrating structured and unstructured data
Implement data validation, quality, traceability, and monitoring processes
Structure and prepare legal, litigation, contractual, and document data
Develop solutions for processing large volumes of documents and unstructured information
Collaborate with Data Scientists, AI professionals, Technology teams, and Legal specialists
Ensure security, governance, access control, and compliance with Brazil’s LGPD data protection law
Identify opportunities to optimize performance, costs, and efficiency across the data infrastructure

Requirements

What you’ll need

Solid experience in Data Engineering and data solution architecture
Proficiency in SQL and Python for data manipulation, transformation, and processing
Experience developing ETL/ELT pipelines
Knowledge of Lakehouse architecture and the Medallion model (Bronze, Silver, and Gold)
Experience with Apache Spark and PySpark
Knowledge of cloud-based data storage and processing platforms
Experience integrating and processing structured and unstructured data
Knowledge of data modeling and building Data Lakes and Data Warehouses
Experience with pipeline orchestration tools such as Apache Airflow or similar technologies
Knowledge of data governance, quality, lineage, and security
Familiarity with preparing data for Machine Learning models and Large Language Models (LLMs)
Experience with Generative Artificial Intelligence projects and LLM-based solutions (a plus)
Knowledge of Retrieval-Augmented Generation (RAG) architectures (a plus)
Experience with document processing, OCR, and extracting and structuring textual information (a plus)
Knowledge of vector databases and embedding techniques (a plus)
Experience working with legal, litigation, contractual, or banking-sector data (a plus)
Knowledge of data and AI services on AWS, Azure, or Google Cloud (a plus)
Experience with DataOps and CI/CD practices applied to Data Engineering (a plus)

Benefits

Comp & perks

This position is also open to people with disabilities (PwD)