Role overview

Qualifications

Proven experience in building and optimizing data pipelines
Strong proficiency in Python, PySpark, and AWS Glue
Experience with Apache Airflow and SQL
Exceptional problem-solving skills

Responsibilities

Build, optimize, and scale data pipelines and infrastructure
Design, operationalize, and monitor ingest and transformation workflows
Collaborate with platform and AI/ML teams for workflow automation
Integrate pipeline health and metrics into engineering dashboards

Key facts

Remote from: Latin America
Full time
Data Engineer
English

Hard skills

Python (Programming Language) Apache Airflow Amazon Web Services Python (Programming Language) AWS Glue Apache Airflow SQL (Programming Language) SQL (Programming Language) Amazon Athena PostgreSQL TypeScript Data Modeling

Other skills

Problem Solving
Team Leadership

About the company

Wizdaa

Information Technology & Services

Wizdaa, formerly known as PrideLogic, excels in creating world-class development teams and extending operational runways for innovative startups. We source, place, and pay top-tier developers who operate within U.S. time zones at highly competitive rates. Recognizing the uniqueness of each startup, we provide tailored solutions to meet specific needs, ensuring every client receives bespoke services that drive success.

Company details

Company typeStartup

IndustryInformation Technology & Services

Company size11 - 50

Links

Website LinkedIn See all jobs

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Job description

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.

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