Responsibilities for the senior members of the Data Architecture and Governance team
- Work collaboratively to develop a coherent data strategy that enables RTX to scale far beyond its current secure data capabilities. Working closely with all business units at RTX, the role will drive data lineage, security, product and platform initiatives as well as data collaboration.
- Work closely with the RTX Enterprise Services teams and the business units to develop the master data management plan for RTX enterprise data, including security, locations, data flows, and data availability.
- As a lead team member, develop a conceptual secure data infrastructure to support data lineage, data quality, data stewardship, data integration, data migration, and system collaboration. This data infrastructure will be further developed in collaboration with the RTX business units. This will include a set of guidelines and standards which ensure that the RTX data assets are managed appropriately, and that they conform to security/federal/DoD guideline principles for stewardship and quality.
- Extend the defined RTX data vision and influence members of RTX Enterprise Services as well as the business units. Work closely with all businesses at RTX to grow the products and capabilities to further the company goals, reviewing potential cost savings and growing revenue.
- Be technical, security aware, analytical, creative, and collaborative, creating data driven solutions that drive for simplicity, efficiency and secure operating standards.
- Describe how data flows from corporate transactions, through the various layers of transformation and integration, through operational data stores, all the way to the decision-support applications that query the data warehouse/lakes or some other data structure optimized for reporting and analytics.
- Lead the identification and complete small-scale enterprise-wide, data reuse projects in concert with data modeling tool improvement and accuracy (inclusive of AI and ML).
- Work with team members and business unit members on data definitions that come from a catalog with data relationships that come from the data models.
- Lead the identification of an enterprise data cataloging tool/capability as well as an MDM/MDG tool.
- Lead and document what the RTX data model (s) will look like, where are problems are, and adding a top-down component to discover what the priorities are for Master Data Model/Master Data Governance.
The Data Dozen – What the team members, especially leaders, will be asked to push
- Data lineage - document the journey our data takes from its creation through its transformations over time. Select and describe a dataset’s origin, movement, characteristics and quality. Understand the point of creation to the point of consumption.
- Know the road our data takes, starting with creation, include the who, what, where, when, why, and how of data.
- Be able to document at each point of consumption/transformation, operation to operation what took place.
- Be able to identify what happened at each step of the data journey and be able to prove that the data, although potentially transformed, was not manipulated.
- Develop a means of data quality proof (i.e. row count, access, logs, etc.).
- Determine the movement of data, structured vs non-structured.
- Validate the logical data layers (details) to determine the holistic vision (the abstract layer that lives above our data) that aligns to the architecture (not the implementation).
- Determine the data duplication, harmonization and longer-term governance.
- Understand the data duplication, not to repair data, understanding the diversity of data and any integration point amongst our business units.
- Understand data to provide quality to applications and users.
- Agree to the short- and long-term data outcomes for the enterprise and business units.
- Sell the longer-term plan to the senior management sponsor(s), finding the drivers, risk controls, operational efficiencies, financial gains and cost savings.
Mission to Provide to RTX
- A secure enterprise data governance and architecture framework that provides secure, defined, quality data whenever and wherever needed in a cost-effective, reusable, and repeatable manner
- A well-defined and managed platform of secure quality data resources (i.e. data lake, warehouse, etc.…)
- Enterprise-approved data definitions, with identified authoritative source, and an understanding of the security, sensitivity, lineage, accuracy and quality of the data.
- Improve the efficiency, increase the profitability and lower the business risks to RTXs’ business units by ensuring that the highest quality data is delivered via a company-wide data governance strategy.
12 Years Experience with BS or BA Degree in a technical program desired
Or Advanced Degree with 10 years experience desired
REMOTE WORK AVAILABLE
Required Immigration Status: