Data Engineer

Há 4 dias

Brasília, Brasil HeartCentrix Solutions Tempo inteiro

We are seeking a highly skilled
Python Data Engineer with an AI/ML focus
to join our client's growing data & analytics team in Brazil. This role is ideal for someone who loves building scalable data pipelines, operationalizing machine learning workflows, and partnering closely with data scientists to bring models into production.
You will design, develop, and maintain data infrastructure that powers AI-driven insights across the organization, including data models and pipelines that run through
Snowflake
. This is a fully remote position working with cross-functional product, engineering, and analytics teams.
Key Responsibilities
Build, optimize, and maintain
ETL/ELT pipelines
using Python, modern data engineering frameworks, and
Snowflake
as a central data warehouse.
Architect and manage
data workflows
, ensuring accuracy, scalability, and reliability.
Work closely with data scientists to
deploy, monitor, and tune machine learning models
.
Develop
feature engineering pipelines
, preprocessing workflows, and model-serving APIs.
Integrate data from various sources (APIs, databases, cloud storage, streaming platforms).
Implement
MLOps best practices
including versioning, CI/CD for ML, and automated retraining workflows.
Optimize data storage, compute usage, and performance within
Snowflake
and cloud-native tools (AWS, GCP, or Azure).
Create and maintain documentation, data catalogs, and operational guides.
Monitor data system performance and recommend improvements.
Required Skills & Experience
3–7+ years of experience as a
Data Engineer
,
Python Engineer
, or similar backend/data role.
Strong proficiency in
Python
, including building production-grade data pipelines.
Experience with
Snowflake
—data modeling, Snowpipe, tasks, streams, stored procedures, and performance optimization.
Experience with
AI/ML workflows
: feature engineering, inference pipelines, or deploying models.
Proficiency in
SQL
and relational databases (PostgreSQL, MySQL, SQL Server).
Hands-on experience with at least one cloud platform (
AWS
,
GCP
, or
Azure
).
Experience using data orchestration tools like
Airflow
,
Prefect
, or
Dagster
.
Familiarity with MLOps tools such as
MLflow, Kubeflow, SageMaker, Vertex AI
, or similar.
Strong understanding of data modeling, data warehousing, and distributed systems.
Preferred Qualifications
Experience with
Spark
,
Databricks
, or other big-data processing tools.
Experience ingesting and transforming data at scale on
Snowflake
, including optimization of virtual warehouses.
Familiarity with
Kafka
,
Kinesis
, or other streaming platforms.
Understanding of CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).
Exposure to deep learning frameworks (TensorFlow, PyTorch).
Experience working with Brazilian clients or LATAM distributed engineering teams.

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