Sr Data and AI Engineer
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ai engineering
- Posted
Skills
Full description
As a Sr Data and AI Engineer, you will work closely with architects, cloud engineers, and clients to design and deliver modern data platforms that power analytics, machine learning, and generative AI initiatives. You will help build scalable data lakes, warehouses, pipelines, and cloud-native architectures, transforming complex business requirements into secure, production-ready solutions. This is a hands-on engineering role focused on delivering impact through automation, Infrastructure as Code (IaC), and CI/CD best practices.
Location: LATAM 100% Remote. Working hours are based on the US Pacific Time Zone. Minimum 6-hour overlap
About the Company:
Abstra is a fast-growing, Nearshore Tech Talent services company, providing top Latin American tech talent to U.S. companies and beyond. Founded by U.S.-bred engineers with over 15 years of experience, Abstra specializes in sourcing skilled professionals across a wide range of technologies to meet our clients’ needs, driving innovation and efficiency.
Key Responsibilities:
- Collaborate with architects and customers to design and implement data pipelines, platforms, lakes, warehouses, and architectures
- Deliver enterprise-level ML and GenAI solutions via IaC and CI/CD
- Continuous learning: staying up to date on AWS (including certifying) as well as awareness of GenAI developments
- Mentoring and guiding junior engineers, cross-team collaboration with cloud engineers
- Build and maintain generic, repeatable data products for use in future consulting engagements
Required Qualifications:
- 5+ years in one of the domains (data engineering or AI/ML)
- At least one year of experience in the other domain
- Experience writing SQL (any dialect), including stored procedures, CTEs, etc.
- Significant programming experience (Python, Scala, Java, etc.) using source control (Git, GitHub, GitLab, Bitbucket, etc.)
- Regularly using at least one major cloud platform: AWS, Azure, GCP
- Confident working directly with customers: you can run a technical conversation, set expectations, and build trust without a project manager in the room
- IaC: Terraform, OpenTofu, CloudFormation, etc.
- Data warehouses: Redshift, Snowflake, BigQuery, etc.
- NoSQL databases and concepts: DynamoDB, Cassandra, Redis, etc.
- Data streaming: Spark, Kafka, Kinesis, etc.
Preferred Qualifications:
- ETL tooling: Airflow, dbt, Glue, Fivetran, etc.