Senior Data Engineer

Job not on LinkedIn

🔥 5 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 25%

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.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Seekerh

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2019

💼 Consulting

🏥 Healthcare

📣 Marketing

Consulting • Healthcare • Marketing

Seekerh is a recruitment and selection consultancy that connects companies with the right professionals through strategic hiring, cultural-fit assessment and rapid, tech-enabled processes. The firm provides tailored recruitment, selection and on-demand talent projects, acting as a strategic partner to support sustainable organizational growth and improved hiring outcomes.

📋 Description

• Design, develop and evolve scalable data pipelines using services from the Azure ecosystem and Databricks • Develop robust data ingestion, transformation and provisioning processes (ETL/ELT), including real-time ingestion scenarios • Implement and optimize solutions using Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), Databricks Jobs/Workflows, Azure Functions, Azure Synapse Analytics and Event Hubs/Event Grid • Design, implement and maintain Data Lakes and Lakehouse architectures (medallion: Bronze/Silver/Gold) on Azure Databricks • Develop solutions using Python, SQL and PySpark with a focus on performance, scalability and data quality • Work with large volumes of structured and unstructured data • Ensure data quality, integrity, security and governance across the entire pipeline, leveraging Unity Catalog and compliance with LGPD • Optimize queries, data processing and data consumption to reduce costs and improve performance • Collaborate with Analytics, Data Science, Software Engineering and Architecture teams to build strategic solutions • Implement monitoring, observability and failure handling in data pipelines • Participate in defining standards, best practices and the evolution of the platform's data architecture • Support analysis and resolution of critical incidents related to the data environment

🎯 Requirements

• Proven experience as a Data Engineer in Azure environments • Strong knowledge of core Azure data services such as Data Factory, ADLS Gen2, Databricks, Synapse Analytics and Azure Functions • Solid experience developing ETL/ELT pipelines • Advanced skills in Python and SQL • Experience with data modeling for analytical environments and Data Lakes/Lakehouse • Knowledge of Apache Spark or PySpark • Experience with version control using Git and CI/CD practices (ideally Azure DevOps) • Knowledge of partitioning, query optimization and distributed processing • Experience with monitoring, observability and troubleshooting of pipelines • Knowledge of cloud data architecture and best practices for security, governance and compliance with LGPD • Strong analytical skills, problem-solving and ability to work in collaborative environments • Nice to have: Experience with Databricks Unity Catalog for data governance and cataloging • Nice to have: Knowledge of Delta Lake and medallion architecture (Bronze/Silver/Gold) • Nice to have: Experience with Azure Data Factory and/or Databricks Workflows / Databricks Asset Bundles (DABs) for orchestration • Nice to have: Experience with event-driven architectures (Event Hubs, Event Grid) • Nice to have: Experience integrating legacy/ERP systems (e.g., SAP) into data pipelines • Nice to have: Knowledge of data quality frameworks (e.g., DQX - Databricks Labs, dbt, Great Expectations) • Nice to have: Experience with real-time data ingestion (e.g., Event Hubs, Kafka) • Nice to have: Experience with Docker and Kubernetes (AKS) • Nice to have: Knowledge of infrastructure-as-code (Terraform or Bicep/ARM Templates) • Nice to have: Experience in Machine Learning, AI and MLOps projects • Nice to have: Experience in large enterprise environments and mission-critical projects • Nice to have: Azure and/or Databricks certifications (e.g., DP-203, Databricks Certified Data Engineer)

🏖️ Benefits

• Contract type can be PJ (contractor, without benefits) or CLT (employee)