Senior Data Platform and Automation Engineer
New
N
NortalData platforms
Location: Latin AmericaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6+ years of software/data engineering experience (or equivalent demonstrated skill); 6+ years of experience with Python, SQL, distributed processing, data modeling, and modern data engineering frameworks.
- Required Skills
- PythonSQLSparkCI/CDData modelingDatabricks
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related STEM field, or a Bachelor's plus a Master's or higher in STEM.
- 6+ years of software/data engineering experience, or equivalent demonstrated skill.
- 6+ years of experience with Python, SQL, distributed processing, data modeling, and modern data engineering frameworks.
- Strong experience with cloud data platforms, data catalogs, metadata, lineage, data quality, and access controls.
- Experience with Databricks, Unity Catalog, Data Lake, Apache Spark, or comparable technologies.
- Experience with CI/CD, automated testing, environment separation, and production deployment.
- Experience building secure APIs, MCP servers, or tools for enterprise and AI-enabled applications.
- Experience with enterprise identity, RBAC, service accounts, secrets management, and least-privilege security.
- Full lifecycle experience across architecture, development, deployment, and production support.
- Nice to have: GitLab CI/CD or comparable, policy-as-code, infrastructure-as-code, and configuration-driven platforms.
- Nice to have: experience building data marketplaces, governance platforms, or internal developer platforms.
- Nice to have: familiarity with privacy, security, regulatory, and AI governance controls, or experience in regulated or risk-sensitive environments.
Responsibilities
- Architect secure, scalable data platform and governance automation capabilities using reusable, configuration-driven patterns.
- Build automated controls for metadata, ownership, lineage, data quality, access, and policy enforcement.
- Implement identity, authorization, least-privilege access, auditability, and credential management.
- Develop secure APIs, MCP tools, and integrations for enterprise and AI-enabled applications.
- Build automated validation, testing, deployment, and monitoring across environments.
- Establish observability for platform health, data quality, policy results, and failures.
- Own production-quality code, tests, documentation, and operational guidance.
- Partner with domain experts, product managers, governance teams, and engineers on technical controls.
- Mentor other engineers and guide technical direction across teams.
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