Mid-Level Data Engineer

Job not on LinkedIn

🔥 14 hours ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Ambev

WebsiteLinkedInAll Job Openings

10,000+ employees

🏭 Manufacturing

📦 Logistics

📣 Marketing

Manufacturing • Logistics • Marketing

Ambev is a Brazilian beverage company that brews, markets and distributes beer, soft drinks and other non-alcoholic beverages across Latin America and beyond. It owns well-known regional brands (e. g. , Skol, Brahma, Antarctica), operates large-scale manufacturing and distribution networks, and is part of the global Anheuser‑Busch InBev group. Ambev focuses on consumer-facing sales, brand marketing, and supply-chain operations for alcoholic and non-alcoholic beverages.

📋 Description

• Act as a Mid-Level Data Engineer at Zé Labs, with the autonomy to lead Data Engineering and Analytics Engineering initiatives within the squad. • Increase the team’s autonomy over pipelines, ingestion, data quality, and observability. • Ensure that data for analytical products is available, reliable, documented, and sustainable. • Build and maintain analytical models with Analytics Engineers, including the Silver layer and semantic layer. • Develop, maintain, and enhance data pipelines. • Integrate data from relational databases, events, messaging systems, and files. • Structure and process data in the Bronze layer. • Increase Zé Labs’ autonomy over pipelines and processes dependent on the corporate Data team. • Define, review, and validate the infrastructure for jobs, workflows, and pipelines. • Review code and technical solutions, promoting engineering best practices. • Guide and support more junior professionals. • Implement and improve logs, metrics, alerts, and monitoring of pipeline health. • Investigate failures, inconsistencies, and performance issues. • Implement error handling, retries, idempotency, reprocessing, and backfills. • Document sources, pipelines, models, business rules, dependencies, and data contracts. • Contribute to SLAs, refresh criteria, and data quality standards. • Assess downstream impacts before making changes to schemas, pipelines, or models. • Participate in prioritizing and organizing the technical backlog with the Data Manager/Data PM. • Participate in technical discussions with Data Engineering, Platform Engineering, and stakeholders.

🎯 Requirements

• Bachelor’s degree completed. • Degrees in Technology, Computer Science, Engineering, Statistics, Mathematics, or related fields are preferred but not required. • Preferably three or more years of experience in Data Engineering, Analytics Engineering, or related fields. • Availability to work remotely. • Proficiency in Python for building pipelines, integrations, or automations. • Proficiency in SQL for querying, transforming, and modeling data. • Practical knowledge of Spark/PySpark or an equivalent distributed processing technology. • Experience building and maintaining data pipelines. • Experience integrating sources such as relational databases, files, APIs, events, or messaging systems. • Experience with modern data platforms or lakehouse architectures. • Knowledge of Git, pull requests, and code review practices. • Experience with error handling, retries, reprocessing, and backfills. • Practical knowledge of testing, observability, and pipeline monitoring. • Databricks, Delta Lake, and Unity Catalog are considered a plus. • AWS and cloud data services are considered a plus. • Databricks Workflows, Airflow, or equivalent orchestration tools are considered a plus. • Knowledge of medallion architecture, CI/CD for data pipelines, data contracts, schema evolution, impact analysis, job optimization, partitioning, compaction, processing costs, and security practices is considered a plus.

🏖️ Benefits

• Medical Insurance • Dental Insurance • Telemedicine • Life Insurance • Gympass • Discount on company products • Christmas basket • Toys for employees’ children • Private pension plan • Meal or Food Voucher • Optional transportation allowance • Attendance bonus (14th salary) • Childcare or Babysitter Allowance • Profit Sharing • Meritocratic and inclusive environment • Development and career growth opportunities