Data Engineer LATAM (Python/PySpark/AWS Glue/Amazon Athena/SQL/Apache Airflow)

Wizdaa; São Paulo; Híbrido; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A leading technology firm is seeking a skilled Data Engineer to build and optimize data pipelines. This fully remote position requires 4+ years of experience with Python and AWS tools. The ideal candidate will have a strong background in managing pipelines and collaborating with AI/ML teams. Compensation is provided in USD, and work hours align with either EST or PT time zones.

Qualificações

• 4+ years of production data engineering experience.
• Deep, hands-on experience with data pipelines.
• Strong SQL skills, particularly in PostgreSQL.

Responsabilidades

• Build and optimize data pipelines using Python and AWS.
• Collaborate with teams to automate workflows.
• Integrate pipeline health into engineering dashboards.

Conhecimentos

Apache Airflow

AWS Glue

PySpark

Python

SQL

PostgreSQL

Descrição da oferta de emprego

Overview

Let’s be direct: We’re looking for a technical powerhouse. If you’re the developer who:

• Is the clear technical leader on your team

• Consistently solves problems others can’t crack

• Ships complex features in half the time it takes others

• Writes code so clean it could be published as a tutorial

• Takes pride in elevating the entire codebase

Then we want to talk to you. This isn’t a role for everyone, and that’s by design. We’re seeking developers who know they’re exceptional and have the track record to prove it.

What you’ll do

• Build, optimize, and scale data pipelines and infrastructure using Python, TypeScript, Apache Airflow, PySpark, AWS Glue, and Snowflake.

• Design, operationalize, and monitor ingest and transformation workflows: DAGs, alerting, retries, SLAs, lineage, and cost controls.

• Collaborate with platform and AI/ML teams to automate ingestion, validation, and real-time compute workflows; work toward a feature store.

• Integrate pipeline health and metrics into engineering dashboards for full visibility and observability.

• Model data and implement efficient, scalable transformations in Snowflake and PostgreSQL.

• Build reusable frameworks and connectors to standardize internal data publishing and consumption.

Required qualifications

• 4+ years of production data engineering experience.

• Deep, hands-on experience with Apache Airflow, AWS Glue, PySpark, and Python-based data pipelines.

• Strong SQL skills and experience operating PostgreSQL in live environments.

• Solid understanding of cloud-native data workflows (AWS preferred) and pipeline observability (metrics, logging, tracing, alerting).

• Proven experience owning pipelines end-to-end: design, implementation, testing, deployment, monitoring, and iteration.

Preferred qualifications

• Experience with Snowflake performance tuning (warehouses, partitions, clustering, query profiling) and cost optimization.

• Real-time or near-real-time processing experience (e.g., streaming ingestion, incremental models, CDC).

• Hands-on experience with a backend TypeScript framework (e.g., NestJS) is a strong plus.

• Experience with data quality frameworks, contract testing, or schema management (e.g., Great Expectations, dbt tests, OpenAPI/Protobuf/Avro).

• Background in building internal developer platforms or data platform components (connectors, SDKs, CI/CD for data).

Additional Information

• This is a fully remote position.

• Compensation will be in USD.

• Work hours are aligned with the EST time zone (9 AM to 6 PM EST) or PT time zone.