Mid-Level Data Engineer – AWS, Databricks

🔥 0 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

☁️ Cloud Engineer

👻 Ghost score 13%

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.

Apply Now

Find Similar Remote Jobs

Keyrus

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1996

🤝 B2B

💼 Consulting

B2B • Data Analytics • Consulting

Keyrus is an international company passionate about leveraging data to make impactful changes in life, society, and the future. With a presence in 18 countries, Keyrus is dedicated to creating meaningful careers for its employees by fostering excellence, trust, creativity, kindness, and fun. Specializing in data analytics, data advisory, and management, Keyrus provides vendor-agnostic solutions and continuous training opportunities through its KLX platform. The company also emphasizes a healthy work-life balance with a range of benefits, including sports events, healthcare plans, and an inclusive work culture. Keyrus is committed to openness and transparency to maintain positive workplace relationships and is driven to innovate and influence the digital future.

📋 Description

• Develop and maintain data ingestion pipelines using Databricks Autoloader • Implement incremental processing and schema evolution • Implement large-scale data processing solutions using Spark Structured Streaming and Spark SQL • Apply partitioning, processing optimization, and Delta Lake • Analyze and optimize the performance and costs of Databricks environments • Implement data quality practices • Work with Git and pull request processes • Prepare technical documentation for developed solutions • Collaborate with business and Analytics teams to ensure data availability, structure, and security • Develop and enhance scalable, efficient, secure, and high-performance data solutions

🎯 Requirements

• Experience in data engineering and processing large volumes of information • Proficiency in Python and Apache Spark • Experience with Databricks • Knowledge of building and maintaining data ingestion pipelines • Experience with Spark Structured Streaming and Spark SQL • Knowledge of Delta Lake and processing optimization techniques • Experience with Git and version control • Knowledge of data quality practices • Preferred: knowledge of modern data architectures and ETL/ELT processes • Preferred: experience with agile methodologies such as Scrum and Kanban • Preferred: experience optimizing costs and performance in scalable data environments • Analytical, self-directed, and skilled at problem-solving • Eagerness to learn new technologies and propose innovative solutions • Excellent communication skills with technical and non-technical audiences • Ability to translate business needs into practical, scalable solutions • Ability to influence decisions and build trusted relationships with stakeholders

🏖️ Benefits

• Remote work environment • Opportunities to develop skills and technical judgment • Collaboration with international teams across multiple geographies • Diversity and multiculturalism culture • Knowledge sharing and continuous improvement

📊 Check your resume score for this job

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

Upload Resume