Data Governance Senior at AST SpaceMobile

Lanham, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

22 May, 26

Salary

0.0

Posted On

21 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Governance, Data Management, Metadata, Lineage, Data Quality, Policy Management, Compliance, Risk Management, Data Cataloging, Stewardship, SQL, Python, Spark, Cloud Data Platforms, Telecom Data, Change Control

Industry

Telecommunications

Description

AST SpaceMobile is building the first and only global cellular broadband network in space to operate directly with standard, unmodified mobile devices based on our extensive IP and patent portfolio and designed for both commercial and government applications. Our engineers and space scientists are on a mission to eliminate the connectivity gaps faced by today’s five billion mobile subscribers and finally bring broadband to the billions who remain unconnected. Position Overview The Data Governance Manager ensures end‑to‑end governance of satellite network data by establishing and maintaining standards, lineage, controls, and data‑quality frameworks that support reliable analytics for BPMS, RAN planning, mobility modeling, and regulatory reporting. This role defines data policies, validates data integrity, manages catalogs and lineage, enforces compliance, and ensures datasets meet engineering and planning requirements for accurate forecasting and operational decision‑making. The position reports to the Director of Network Planning & Analytics. This role is responsible for ensuring the trustworthiness, consistency, and governance of all satellite‑network data used for planning, modeling, and regulatory submissions. The Data Governance Manager establishes governance standards, lineage practices, and quality controls that enable dependable analytics across BPMS, RAN planning, and mobility modeling. By enforcing data‑quality and compliance standards, the role underpins accurate forecasting, defensible regulatory reporting, and sound operational decisions at scale. Key Responsibilities Data Governance Framework & Policy Management Establish data governance models, principles, and operating processes for satellite‑network datasets. Define and enforce data policies, standards, classification rules, lifecycle guidelines, and governance controls. Integrate governance requirements into planning workflows, data pipelines, and change management processes. Metadata, Lineage, Cataloging & Data Quality Maintain data catalog, glossary, metadata repositories, and end‑to‑end lineage for critical planning and mobility datasets. Ensure data discoverability, semantic consistency, and traceability across engineering and analytics systems. Set data quality SLAs/SLOs, implement automated checks, and lead remediation for issues impacting planning accuracy or regulatory reporting. Compliance, Risk Management & Cross‑Functional Alignment Ensure data compliance with regulatory reporting, internal governance, and audit requirements. Maintain audit‑ready artifacts and evidence of lineage, access governance, and data controls. Define stewardship roles, collaborate with planning, engineering, and analytics teams, and align data definitions with system‑level needs. Analytics Enablement, Change Control & Reporting Certify trusted datasets for BPMS analytics, RAN planning, mobility modeling, and forecasting. Govern schema changes, version control, and data lifecycle evolution across platforms. Deliver dashboards and reporting on data quality, lineage completeness, control adherence, risks, and remediation status. Deliverables Data governance charter and operating model; documented policies, standards, and control catalogs. Enterprise data catalog with business glossary, certified data products, and end‑to‑end lineage maps. Data quality framework with rules, SLAs/SLOs, scorecards, monitoring, and remediation workflows. Stewardship model with ownership matrix (RACI), steward roster, and council meeting cadence notes. Approved data models and definitions for BPMS, RAN planning, mobility modeling, and regulatory datasets. Access governance artifacts (classification, RBAC/ABAC matrices), audit logs, and evidence packs. Change management procedures covering schema/versioning, impact assessments, and rollback plans. Quarterly governance dashboards (DQ trends, lineage completeness, incidents, SLA adherence). Regulatory reporting data packs with traceable lineage, control evidence, and sign‑off records. Deployment readiness “data certification” checklists for market activation and ongoing operations. Qualifications Education Bachelor’s degree in Computer Science, Data/Information Systems, Engineering, or a related field. Master’s degree (Data/Information Management, Analytics, or similar) is a plus. Experience 5+ years in data governance, data management, or metadata/lineage/data quality leadership roles. Experience governing analytics for telecom/satellite, networks, or other complex, regulated data environments. Proven track record establishing policies/standards, implementing catalogs/lineage, and enforcing data quality controls. Demonstrated cross‑functional leadership partnering with engineering, analytics, and regulatory stakeholders. Required Technical Expertise Data governance frameworks and artifacts (policies, standards, stewardship, RACI, control catalogs). Metadata/lineage management and data catalog administration (e.g., Microsoft Purview, Collibra, Alation, Apache Atlas, Unity Catalog). Data quality frameworks and tooling (rule‑based and statistical checks; DQ SLAs, scorecards, monitoring, remediation). Master & reference data management (MDM/RDM) and semantic modeling (conceptual/logical/physical). Access governance (RBAC/ABAC), data classification, PII handling, encryption, and audit logging. Cloud data platforms and pipelines (Azure/AWS; Databricks/Spark; Snowflake/Redshift; Synapse/Delta Lake). Practical understanding of network/satellite data domains (telemetry, coverage/traffic KPIs, mobility events, spectrum/logs, cost/deployment data). Professional Skills Structured, detail‑oriented problem solving with a strong documentation mindset. Ability to translate regulatory and engineering requirements into clear data controls and standards. Excellent stakeholder management and communication across technical and non‑technical audiences. Change management leadership for data lifecycle governance and platform evolution. Ability to prioritize in a fast‑paced environment and drive outcomes through influence. Technology Proficiency SQL for profiling and validation; familiarity with Python/Spark for quality rules and data tests. Experience with data catalogs, lineage tools, and DQ platforms; BI tools (Power BI/Tableau) for governance dashboards. Working knowledge of CI/CD for data (versioning, release pipelines) and collaboration tools (Jira/Confluence). Strong proficiency with Microsoft Office Suite (Excel, PowerPoint, Word); Windows/Linux environments. Physical Requirements Ability to work in a standard office or lab environment and operate a computer for extended periods. Occasional travel for cross‑functional workshops, audits, and market activation readiness reviews. This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. AST SpaceMobile is an Equal Opportunity, at will Employer; employment is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.

Responsibilities

The Data Governance Manager establishes governance models, policies, and standards for satellite network data, focusing on lineage, quality controls, and compliance to support reliable analytics for planning and regulatory reporting. This role is responsible for maintaining data catalogs, enforcing data quality SLAs, and ensuring data trustworthiness across engineering and analytics systems.