Senior Data and AI Engineer
New
A
AbstraData and AI
Location:LATAM 100% Remote. Source API remote eligibility restrictions: Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bermuda, Bolivia, Bonaire, Sint Eustatius and Saba, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), Grenada, Guatemala, Guyana, Haiti, Honduras, Jamaica, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela, Virgin Islands, British, Virgin Islands, U.S., Working hours are based on the US Pacific Time Zone. Minimum 6-hour overlapContractSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years in one of the domains (data engineering or AI/ML); at least one year of experience in the other domain
- Required Skills
- AWSPythonSQLGCPGitAzure
Requirements
- Have 5+ years of experience in either data engineering or AI/ML.
- Have at least one year of experience in the other domain.
- Write SQL in any dialect, including stored procedures and CTEs.
- Have significant programming experience with Python, Scala, Java, or similar languages.
- Use source control such as Git, GitHub, GitLab, or Bitbucket.
- Regularly use at least one major cloud platform: AWS, Azure, or GCP.
- Confidently lead technical conversations with customers, set expectations, and build trust.
- Have experience with IaC tools such as Terraform, OpenTofu, or CloudFormation.
- Have experience with data warehouses such as Redshift, Snowflake, or BigQuery.
- Understand NoSQL databases and concepts, including DynamoDB, Cassandra, or Redis.
- Have experience with data streaming tools such as Spark, Kafka, or Kinesis.
Responsibilities
- Collaborate with architects and customers to design and implement data pipelines, platforms, lakes, warehouses, and architectures.
- Deliver enterprise-level ML and GenAI solutions using IaC and CI/CD.
- Stay current with AWS, including certification, and developments in GenAI.
- Mentor and guide junior engineers and collaborate across teams with cloud engineers.
- Build and maintain generic, repeatable data products for future consulting engagements.
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