Join #Ensiteam! 🚀

At Ensitech, we are a custom software development company with more than 20 years of experience delivering high-quality technology solutions.

The Data Governance Engineer (Level 1) is an entry-level, hands-on technical role. You’ll help implement and maintain data governance controls across our cloud-native data platforms and analytics environments. Working under the guidance of senior governance engineers, you’ll build and support data quality checks, metadata and catalog updates, lineage documentation, data classification, and access controls within our data pipelines, warehouse/Lakehouse architecture, and BI platforms.

You’ll work alongside data engineering, architecture, and security teams. Most of your time will go to building, testing, monitoring, and troubleshooting governance controls in Azure data services, orchestration tools, and CI/CD workflows. It’s a chance to build a strong base in enterprise data management while making our data more reliable, secure, and compliant.

Key Responsibilities

Build, test, and maintain automated data quality checks, including profiling, validation rules, and monitoring, within orchestration tools (e.g., Azure Data Factory, Databricks) and warehouse/Lakehouse environments.
Investigate data quality issues and alerts, document root causes, and help carry out fixes with data engineers and data stewards.
Keep the enterprise data catalog current. This includes running and monitoring metadata ingestion, updating technical metadata, linking assets to business glossary terms, and documenting data lineage.
Apply data classification tags, retention rules, and role-based access controls (RBAC) on Azure data platforms and in Power BI, following established standards.
Contribute to version-controlled code and CI/CD deployment pipelines, following team standards for data modeling, certified datasets, and DevOps practices.
Write and maintain technical documentation, runbooks, and standard operating procedures for governance tools and processes.
Join team code reviews, stand-ups, and knowledge-sharing sessions, and grow your technical skills with mentoring from senior engineers.

Minimum Job Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field, or equivalent practical experience.
2–4 years of experience in data engineering, data analytics, data governance, or a related technical role. Internships, co-ops, and academic projects count.
Working knowledge of SQL and basic data modeling concepts (e.g., relational tables, joins, keys, star schemas).
Familiarity with data cataloging tools: Alation, Atlan, Collibra, data.world, etc.
Familiarity with data observability tools: Bigeye, Monte Carlo, Informatica, etc.
Familiarity with cloud data platforms, preferably Microsoft Azure (Azure Data Factory, Databricks/Spark, Power BI), or a strong interest in learning them.
Basic understanding of version control (e.g., Git) and exposure to CI/CD or DevOps concepts.
Awareness of data security basics, such as access controls, least privilege, and handling sensitive data.
Strong attention to detail, good problem-solving skills, and a willingness to learn new tools and take feedback.
Clear written and verbal communication, and the ability to work well with both technical and business teammates.

Preferred Qualifications

Exposure to Python or PySpark for scripting or data processing.
Familiarity with data catalog or governance tools (e.g., Microsoft Purview, Unity Catalog, Collibra, Alation).
Coursework or certifications in data management or Azure (e.g., DP-900, DP-203, DAMA fundamentals).

What We Offer

✅ 100% remote opportunity
✅ Opportunity to work on cutting-edge AI projects
✅ Collaboration with leading Frontier LLM companies
✅ International and innovation-driven environment
✅ Potential contract extension based on performance and project needs