Data Engineer

FCamara Consulting & Training

Data Engineer focused on AI building reliable, scalable infrastructure for Machine Learning applications and Generative AI. Ensuring data quality and enabling efficient data processing pipelines.

Posted 6/3/2026full-timeRemote • 🇧🇷 BrazilMid-LevelSeniorWebsite

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAdvanced SQLScalaApache AirflowdbtPrefectSparkPandasPySparkKafka

Soft Skills

collaborationdata governancedata qualitydata security

Tools & Technologies

DockerKubernetesAWSGCPAzureBigQuerySnowflakeRedshiftS3GCS

Industry Keywords

data lakesdata warehousesNoSQL databasesvector databasesembedding pipelinesvector indexingRetrieval-Augmented Generationfeature storesbatch processingstreaming ingestion

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudDockerGoogle Cloud PlatformKafkaKubernetesNoSQLPandasPySparkPythonScalaSparkSQL

About the role

Key responsibilities & impact

Build batch and streaming ingestion pipelines
Design and structure data lakes and data warehouses
Create datasets optimized for machine learning (ML)
Implement embedding pipelines
Build vector indexing for RAG (Retrieval-Augmented Generation)
Ensure data quality, governance, and security
Optimize storage and processing costs
Collaborate with AI Engineers to design feature stores

Requirements

What you’ll need

Python
Advanced SQL
Scala (optional)
Apache Airflow
dbt
Prefect
Spark
Pandas
PySpark
Data lakes (S3, GCS, Azure Blob)
Data warehouses (BigQuery, Snowflake, Redshift)
NoSQL databases
Vector databases (Pinecone, Weaviate, FAISS)
Kafka
Pub/Sub
Docker
Kubernetes
Cloud (AWS, GCP, or Azure)

Benefits

Comp & perks

Training and development program
Community and social initiatives that promote development
Diversity, Respect, and Ethics