Data Engineer – DataOps, AWS

🔥 9 minutes 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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SysMap Solutions

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

💼 Consulting

📣 Marketing

🤖 Artificial Intelligence

Consulting • Marketing • Artificial Intelligence

SysMap Solutions is a services company devoted to offering technological development to its customers since 1997. With a focus on cloud solutions, Salesforce, mobile development, CRM, user experience, DevOps, machine learning, and digital transformation, SysMap Solutions leverages its extensive experience to craft complex codes and systems that meet client demands. The company prides itself on its ability to deliver tailored solutions, ensuring that the final product is precisely aligned with customer needs. In the Age of Information, SysMap Solutions stands out as a knowledgeable partner in technology.

📋 Description

• Develop, enhance, and maintain batch and streaming data pipelines. • Design and implement data engineering solutions using Databricks and AWS services. • Apply DataOps practices focused on process automation, standardization, quality, and reliability. • Develop and maintain CI/CD processes for pipelines, notebooks, jobs, and data components. • Implement monitoring, observability, logging, and alerting mechanisms. • Ensure data quality, integrity, availability, and traceability. • Work with the processing and transformation of large volumes of data. • Develop solutions using Apache Spark / PySpark and SQL. • Integrate different data sources and systems. • Contribute to the definition and evolution of data architecture. • Support initiatives to optimize infrastructure and cloud performance and costs. • Identify and resolve performance issues, pipeline failures, and data inconsistencies. • Collaborate with Data Analysts, Data Scientists, Architects, Engineering teams, and business stakeholders. • Contribute to the definition of data engineering standards, best practices, and governance.

🎯 Requirements

• Solid experience in Data Engineering. • Experience developing ETL/ELT processes and data pipelines. • Advanced knowledge of SQL. • Experience with Python and/or PySpark. • Knowledge of large-scale data architecture and processing. • Experience working with structured and semi-structured data. • Hands-on experience with Databricks. • Knowledge of Apache Spark / PySpark. • Experience with Delta Lake / Delta Tables. • Knowledge of Databricks Jobs, Workflows, and processing mechanisms. • Knowledge of workload performance best practices and optimization techniques. • Strong sense of ownership and commitment to delivery. • Proactive and collaborative mindset. • Ability to take on challenges and see them through to completion. • Strong communication skills and ability to work effectively with multidisciplinary teams. • Curiosity and a continuous desire to learn and grow. • Mindset focused on building and continuous improvement.

🏖️ Benefits

• No benefits, perks, or additional compensation are explicitly stated in the posting.