Senior Data Engineer – Databricks

Job not on LinkedIn

🔥 2 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 22%

What it means: the chance that no one is really hiring for this job.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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AVANTTi

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

🏭 Manufacturing

Consulting • Logistics • Manufacturing

AVANTTi is a Brazilian technology services company that helps organizations maximize the value of their technology and innovation projects through its VMO (Value Management Office) methodology. It offers IT staffing and hunting (outsourcing/bodyshop), rapid squad formation, a software factory for technologies like ABAP, Java and . NET, and portfolio/SAFe management to support digital transformation across sectors such as banking, manufacturing, logistics, retail and education. The company operates from Curitiba, São Paulo and Rio de Janeiro and focuses on B2B delivery, enterprise IT solutions and talent allocation.

📋 Description

• Develop and implement data engineering solutions using Databricks • Build, maintain, and optimize scalable pipelines for Batch, Micro-batch, and Streaming processing • Implement solutions with Apache Spark, Delta Lake, Delta Live Tables (Lakeflow Declarative Pipelines), Unity Catalog, and Apache Iceberg • Develop YAML-driven pipelines • Implement incremental ingestion and automated processing with Databricks Auto Loader • Develop and manage workflows and orchestrations with Databricks Jobs/Workflows, Apache Airflow, or dbt • Ensure data quality, integrity, traceability, and observability • Implement pipeline auditing, monitoring, and validation • Participate in technical design and architecture sessions • Translate complex requirements into structured technical activities, ensuring quality and timely delivery • Collaborate with Solution Architects and cross-functional teams to implement customer data platforms • Participate in the Databricks Center of Excellence by creating accelerators, reusable components, and technical improvements • Track trends and new capabilities in the Databricks ecosystem, applying continuous innovation

🎯 Requirements

• Strong experience in Data Engineering, with at least 2 years of hands-on experience developing and designing pipelines using Databricks • Proficiency in pipeline development and data processing in distributed environments • Hands-on experience with Databricks, Delta Lake, Delta Live Tables (Lakeflow Declarative Pipelines), Unity Catalog, Apache Iceberg / Uniform, and Databricks Auto Loader • Experience building scalable, configuration-driven YAML pipelines • Knowledge of Batch, Micro-batch, and Streaming ingestion and processing patterns • Experience with Databricks Jobs/Workflows, Apache Airflow, or dbt • Knowledge of data quality, auditing, and observability, including Databricks, Great Expectations, Collibra, or dbt • Proficiency in Apache Spark, Presto, and Amazon EMR • Experience with Amazon Redshift, Snowflake, and Google BigQuery • Strong knowledge of SQL, Stored Procedures, and object-oriented programming • Experience with Python, PySpark, or Java • Familiarity with DevOps and CI/CD, including Databricks Asset Bundles, automated validation, and testing • Knowledge of version control, automation, and deployment of data solutions • Analytical, curious, and focused on solving complex problems • Technical autonomy and the ability to lead activities with minimal supervision • Comfortable working in cross-functional teams • Ability to break down complex technical challenges into structured deliverables • Proactive in identifying opportunities for improvement and innovation • Strong communication skills and the ability to share knowledge with the team • Commitment to quality, efficiency, and meeting delivery deadlines

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