Data Engineer

TurnKey Tech Staffing

Brasil

Presencial

BRL 133 920 - 200 880

Tempo integral

14 dias+

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Resumo da oferta

A tech staffing company in Brazil is looking for a skilled Data Engineer to develop and support data pipelines. The role involves collaboration across teams, data modeling, and ensuring data quality. Candidates should have a Bachelor's in Computer Science and experience in data engineering, along with strong skills in Python and SQL. The position offers a full-time employment opportunity.

Qualificações

3-5 years of experience in data engineering.
Experience in building scalable data pipelines.
Software engineering mindset with CI/CD practices.

Responsabilidades

Design and maintain scalable data pipelines.
Develop and support data models and warehouse tables.
Collaborate with cross-functional teams on data use.

Conhecimentos

Python

SQL

Data modeling techniques

Analytical problem solver

Attention to detail

Formação académica

Bachelor’s degree in Computer Science or related field

Ferramentas

Snowflake

Postgres

DBT

Airflow

Docker

Kubernetes

Kafka

Descrição da oferta de emprego

Overview

Niche is the leader in school search. Our mission is to make researching and enrolling in schools easy, transparent, and free. With in-depth profiles on every school and college in America, 140 million reviews and ratings, and powerful search tools, we help millions of people find the right school for them. We also help thousands of schools recruit more best-fit students, by highlighting what makes them great and making it easier to visit and apply. Niche is all about finding where you belong, and that mission inspires how we operate every day. We want Niche to be a place where people truly enjoy working and can thrive professionally.

About the Role

Niche is looking for a skilled Data Engineer to join the Data Engineering team. Youʼll build and support data pipelines that can handle the volume and complexity of data while ensuring scale, data accuracy, availability, observability, security, and optimum performance. Youʼll be developing and maintaining data warehouse tables, views, and models, for consumption by analysts and downstream applications. This is an exciting opportunity to join our team as weʼre building the next generation of our data platform, and engineering capabilities. Youʼll be reporting to the Manager, Data Engineering (Core).

What You Will Do

Design, build, and maintain scalable, secure data pipelines that ensure data accuracy, availability, and performance.
Develop and support data models, warehouse tables, and views for analysts and downstream applications.
Ensure observability and quality through monitoring, lineage tracking, and alerting systems.
Implement and maintain core data infrastructure and tooling (e.g., dbt Cloud, Airflow, RudderStack, cloud storage).
Collaborate cross-functionally with analysts, engineers, and product teams to enable efficient data use.
Integrate governance and security controls such as access management and cost visibility.
Contribute to platform evolution and developer enablement through reusable frameworks, automation, and documentation.

What We Are Looking For

Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.
3-5 years of experience in data engineering.
Demonstrated experience of building, and supporting large scale data pipelines – streaming and batch processing.
Software engineering mindset, leading with the principles of source control, infrastructure as code, testing, modularity, automation, CI/CD, and observability.
Proficiency in Python, SQL, Snowflake, Postgres, DBT, Airflow.
Experience of working with Google Analytics, Marketing, Ad & Social media platform, CRM/Salesforce, and JSON data; Government datasets, and geo-spatial data will be a plus.
Knowledge and understanding of the modern data platform, and its key components – ingestion, transformation, curation, quality, governance, and delivery.
Knowledge of data modeling techniques (3NF, Dimensional, Vault).
Experience with Docker, Kubernetes, Kafka will be a huge plus.
Self-starter, analytical problem solver, highly attentive to detail, effective communicator, and obsessed with good documentation.

First Year Plan

During the 1st Month:

Immerse yourself in the company culture, and get to know your team and key stakeholders.
Build relationships with data engineering team members, understand the day to day operating model, and stakeholders that we interact with on a daily basis.
Start to learn about our data platform infrastructure, data pipelines, source systems, and inter-dependencies.
Start participating in standups, planning, and retrospective meetings.
Start delivering on assigned sprint stories and show progress through completed tasks that contribute to team goals.

Within 3 Months:

Start delivering on assigned data engineering tasks to support our day to day, and roadmap.
Start troubleshooting production issues, and participating in on-call activities.
Identify areas for improving data engineering processes, and share with the team.

Within 6 Months:

Contribute consistently towards building our data platform, which includes data pipelines, and data warehouse layers.
Start to independently own workstreams whether it is periodic data engineering activities, or work items in support of our roadmap.
Deepen your understanding, and build subject matter expertise of our data & ecosystem.

Within 12 Months:

Your contributions have led to us making significant progress in implementing the data platform strategy, and key data initiatives to support the company’s growth.
Youʼve established yourself as a key team member with subject matter expertise within data engineering.

Seniority level