Senior Data Engineer

SysMap Solutions

. Design, develop, and maintain scalable, efficient data pipelines .

Posted 10/23/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing scalable data pipelines using Cloudera, Databricks, and AWS services, with strong proficiency in Python, SQL, and PySpark. Skilled in implementing ETL/ELT processes and ensuring data quality, security, and governance across diverse data architectures.

Highest-signal resume keywords

Senior Data Engineer ExperienceCloudera and Databricks KnowledgeAWS Data Services ExperienceAdvanced SQL SkillsETL/ELT Processes Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLPySparkApache SparkETL ProcessesData Lake ArchitectureData ModelingDelta LakeApache KafkaCI/CD Practices

Tools & Technologies

ClouderaDatabricksAWS GlueAmazon S3Amazon RedshiftAmazon LambdaAmazon AthenaApache AirflowGitHadoop

Industry Keywords

Data Pipeline MonitoringData GovernanceData QualityData SecurityDistributed ProcessingData IntegrationData ArchitectureData TransformationReal-Time Data ProcessingData Platform Migration

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSCloudETLHadoopHDFSKafkaPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design, develop, and maintain scalable, efficient data pipelines
Implement data ingestion, transformation, and integration processes using batch and streaming architectures
Develop and optimize solutions using Cloudera, Databricks, and AWS services
Create data processing and transformation routines using Python, SQL, and PySpark
Develop and maintain ETL/ELT processes
Work with Data Lake, Lakehouse, and distributed processing architectures
Integrate diverse data sources while ensuring information quality, consistency, and reliability
Monitor and optimize the performance of pipelines, jobs, and queries
Apply best practices in data security, governance, cataloging, and lineage
Contribute to the evolution of the data architecture and the continuous improvement of processes
Collaborate with architecture, analytics, data science, and business teams

Requirements

What you’ll need

Solid experience as a Senior Data Engineer
Knowledge of Cloudera and Databricks, with experience processing and transforming large volumes of data
Knowledge of AWS (Amazon Web Services) and its core services applied to data engineering
Advanced SQL skills and experience with Python and PySpark
Experience with Apache Spark and distributed processing
Knowledge of ETL/ELT processes and tools
Experience with Data Lake and Lakehouse architectures
Knowledge of data modeling and integrating diverse information sources
Experience with version control using Git
Knowledge of data pipeline monitoring, troubleshooting, and optimization
Experience with AWS data services such as Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, and Amazon Athena
Knowledge of data processing and orchestration services in cloud environments
Experience with Delta Lake and Hadoop ecosystem technologies such as Hive, HDFS, and Impala
Knowledge of Apache Kafka and real-time data processing
Experience with Apache Airflow or similar orchestration tools
Knowledge of CI/CD practices, infrastructure as code, and automation
Experience with data governance, quality, security, and observability
Experience working on data platform migration, modernization, and integration projects

Benefits

Comp & perks

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