Data Engineer (AI)

TL;DR

Data Engineer (AWS/AI): Designing and building modern data platforms to support large-scale risk and compliance initiatives with an accent on scalable data systems and real-time pipelines. Focus on implementing robust ETL/ELT workflows, optimizing big data infrastructure on AWS, and automating manual data processes.

Location: Remote. Must be based in Colombia, Argentina, Brazil, Georgia, Poland, or Ukraine

Company

AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence.

What you will do

• Design and optimize scalable data infrastructure for risk and compliance workloads.
• Develop batch and streaming pipelines using modern big data technologies.
• Implement ETL/ELT workflows across diverse structured and unstructured data sources.
• Build high-throughput, low-latency systems using AWS services including EMR, Redshift, S3, Glue, Lambda, and Kinesis.
• Partner with data scientists and analysts to deliver reliable and well-documented datasets.
• Automate manual reporting, analytics, and data preparation processes.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or similar.
• 3 or more years of hands-on experience in data engineering or related fields.
• Strong proficiency in SQL and data modeling for analytics and warehousing.
• Experience with big data technologies such as Hadoop, Hive, Spark, HBase, or EMR.
• Basic scripting skills in Python or Scala.
• Must be based in Colombia, Argentina, Brazil, Georgia, Poland, or Ukraine.

Nice to have

• Experience with AWS data services (Redshift, S3, Glue, EMR, Kinesis, Firehose, and Lambda).
• Experience with non-relational data stores (document, key-value, column-family, or graph databases).
• Strong understanding of data governance, quality, and security best practices.
• Familiarity with machine learning concepts.

Culture & Benefits

• Opportunity to shape real-world AI-driven projects across various industries.
• Work as part of a global team with equal opportunities for cross-continental collaboration.
• Inclusive environment prioritizing continuous learning and ethical AI standards.