Senior Data Engineer – Data Architecture

🕒 September 1

🇧🇷 Brazil – Remote

⏳ Contract/Temporary

🟠 Senior

🚰 Data Engineer

👻 Ghost score 29%

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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CrafTech Smart Solutions

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2010

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

CrafTech Smart Solutions is a technology consultancy specializing in digital transformation, IT staff augmentation, and custom innovation solutions. With around 15 years of experience and a large pool of outsourced professionals, the company operates an innovation lab to develop tailored software, systems modernization, and AI integrations for enterprise clients across sectors such as logistics, fintech, and retail.

📋 Description

• Design, build, and maintain ingestion and transformation pipelines orchestrated with Apache Airflow, using consistent standards for retries, idempotency, alerting, and SLAs • Develop and evolve dbt transformation models in the data warehouse, organizing staging, intermediate, and marts layers with tests and documentation • Implement ingestion from heterogeneous sources, including transactional databases, third-party APIs, regulatory files, and operational spreadsheets • Instrument data observability, including freshness, volume, contract violations, and source-to-target reconciliation • Define and advocate for the warehouse data model, including keys, grain, historization (SCD), and the handling of retroactive corrections • Establish distribution, sort-order, and partitioning standards in the MPP environment and ensure their adoption • Design data layers and contracts between teams, defining the source of truth, write permissions, and exposure for BI • Lead performance and cost tuning, including plan analysis, queues/WLM, concurrency, maintenance, query rewrites, and materializations • Evaluate and recommend technologies based on explicit trade-offs, costs, and exit costs • Implement automated quality controls and reconciliations for customer reporting and regulatory responses • Ensure end-to-end lineage and traceability, from the source and code version through to the figures displayed in dashboards • Apply access controls, sensitivity-based segregation, and compliance with LGPD, CVM, BACEN, BSM, and internal compliance policies • Document architectural decisions (ADRs) and keep the data dictionary up to date

🎯 Requirements

• Bachelor’s degree completed • Truly advanced SQL: window functions, recursive CTEs, execution plan analysis, and diagnosis of data skew and disk spills • Python for data engineering: modular, testable, version-controlled code—not just notebooks • Familiarity with pandas/Polars, typing, and automated testing • Apache Airflow in production: DAG authoring, sensors, backfills, dependency management, and failure handling • Cloud-based MPP data warehouse—Amazon Redshift preferred; Snowflake, BigQuery, or Databricks accepted, with a willingness to deepen expertise in Redshift • dbt or an equivalent version-controlled transformation tool with testing capabilities • Dimensional modeling (Kimball) with hands-on expertise: fact vs. dimension, grain, Type 1/Type 2 SCDs, bridge tables, and snapshots • Git and a code review culture; CI/CD applied to data • Performance modeling and diagnosis: you can explain why a query is slow and demonstrate the fix with before-and-after metrics • Experience in the financial services industry is a plus

🏖️ Benefits

• 20 days of planned leave • TotalPass