Data Engineer – Data Platforms & AI Tooling
New
I
ITXData Engineering, AI
This role is limited to candidates based in LATAM.ContractSenior
Salary5,400 - 7,900 USD per month
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Job Details
- Languages
- Professional English proficiency.
- Experience
- 4+ years
- Required Skills
- DockerPythonSQLSnowflakeAirflowTerraformdbtDatabricks
Requirements
- 4+ years of experience in Data Engineering, Backend Engineering, or a related field.
- Strong Python and SQL skills.
- Experience building and operating production data pipelines.
- Experience with cloud data platforms such as Snowflake, Databricks, BigQuery, Redshift, Microsoft Fabric, or similar.
- Experience with dbt or comparable data transformation tools.
- Experience with orchestration tools such as Airflow, Dagster, Prefect, or similar.
- Experience with data modeling techniques such as dimensional modeling, SCDs, or Data Vault.
- Experience working with at least one major cloud provider (Azure, AWS, or GCP).
- Experience supporting, integrating, or developing AI-powered and Agentic AI solutions.
- Familiarity with Retrieval-Augmented Generation (RAG) concepts and vector databases (e.g., Pinecone, Weaviate).
- Experience with CI/CD, Docker, and Infrastructure as Code (Terraform).
- Professional English proficiency.
Responsibilities
- Build and maintain scalable batch and streaming data pipelines that ingest and transform data from applications, databases, APIs, event streams, and third-party systems.
- Develop trusted, reusable data products that support analytics, business applications, and AI solutions.
- Design and maintain data models that enable reporting, analytics, and AI consumption.
- Build AI-facing integration layers, including MCP servers and similar interfaces that allow AI agents to securely access data and platform capabilities.
- Collaborate with AI, platform, and infrastructure teams to support production-grade Agentic AI solutions.
- Implement data quality, testing, monitoring, observability, and lineage across data pipelines and AI integrations.
- Ensure data governance, privacy, security, and access-control standards are applied consistently.
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