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.
- Familiarity with ML concepts (random forests, neural nets, etc.) and common frameworks: scikit-learn, TensorFlow, PyTorch, etc.
- Containerization: Docker, Kubernetes, etc.
- Data visualization: QuickSight, Tableau, Power BI, etc.
What We Offer:
- Competitive compensation paid in USD.
- 20 days of paid time off (PTO) per year.
- Opportunities for professional growth and career development.
- Company-provided equipment.
- A collaborative, inclusive, and multicultural work environment.
- The opportunity to contribute to meaningful projects alongside a talented and supportive team.
Pre-Employment Verification
As part of our standard onboarding process, candidates who successfully complete the interview process and accept an employment offer will be required to complete an employment verification check, and background check. This process will confirm job titles and dates of employment with two previous employers and is a standard requirement for all new employees joining the company.
Skills Required
- 5+ years of experience in data engineering or AI/ML
- At least 1 year of experience in the other domain between data engineering and AI/ML
- Experience writing SQL, including stored procedures and common table expressions
- Significant programming experience with Python, Scala, Java, or similar languages
- Experience using source control such as Git, GitHub, GitLab, or Bitbucket
- Regular use of at least one major cloud platform: AWS, Azure, or GCP
- Ability to work directly with customers, lead technical conversations, set expectations, and build trust
- Infrastructure as Code experience with Terraform, OpenTofu, CloudFormation, or similar tools
- Experience with data warehouses such as Redshift, Snowflake, or BigQuery
- Knowledge of NoSQL databases and concepts, such as DynamoDB, Cassandra, or Redis
- Experience with data streaming technologies such as Spark, Kafka, or Kinesis
- Experience with ETL tools such as Airflow, dbt, Glue, or Fivetran
- Familiarity with machine learning concepts and frameworks such as scikit-learn, TensorFlow, or PyTorch
- Experience with containerization technologies such as Docker or Kubernetes
- Experience with data visualization tools such as QuickSight, Tableau, or Power BI
What We Do
At Abstra, we bridge the gap between North American companies and Latin America’s top talent. With over 15 years of experience in the U.S. market and US-bred founders leading the way, we focus on building long-term partnerships to achieve your organization’s unique goals, fueling your growth with flexible tech solutions and highly qualified professionals.
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