Data Operations Manager

Date Posted:

2024-10-02

Country:

United States of America

Location:

VA543: 22270 Pacific Blvd, Dulles 22270 Pacific Boulevard Building CC5, Sterling, VA, 20166-6924 USA

Position Role Type:

Hybrid

You have been redirected to RTX’s career page as we have recently transitioned from RTX to become a standalone company, which provides us with greater autonomy and opportunities for growth. As a prospective employee of Nightwing, you’ll have the chance to contribute to our continued success and shape the future of our cybersecurity, intelligence, and services offerings.

Nightwing provides technically advanced full-spectrum cyber, data operations, systems integration and intelligence mission support services to meet our customers’ most demanding challenges. Our capabilities include cyber space operations, cyber defense and resiliency, vulnerability research, ubiquitous technical surveillance, data intelligence, lifecycle mission enablement, and software modernization. Nightwing brings disruptive technologies, agility, and competitive offerings to customers in the intelligence community, defense, civil, and commercial markets.

We are seeking an Data Operations Manager. This role is essential to foster the adoption of Data Mesh principles across the organization by advocating for decentralized data ownership, helping domain teams become proficient in creating and managing data products, and promoting a self-serve data platform culture. The Enabling Team Lead will act as a trusted advisor and guide domain teams in their journey toward data autonomy, ensuring they are equipped with the right tools, practices, and understanding to excel in a federated data ecosystem.

Key Responsibilities:

Data Mesh Advocacy: Act as an internal consultant to educate and promote Data Mesh principles, helping domain teams transition to data-as-a-product thinking and decentralized data ownership.

Support Domain Teams: Temporarily embed within domain teams to understand their needs, establish learning environments, and provide expertise on data analytics and self-serve platform usage without directly creating data products.

Upskilling & Training: Lead efforts to upskill domain team members in data analytics, engineering, and product development, ensuring they can operate independently within the Data Mesh framework.

Develop Learning Materials: Create and share best practices, tutorials, walking skeletons, and other learning resources to support teams, fostering continuous knowledge sharing across the organization.

Cross-team Collaboration: Partner with data engineering, analytics, and governance teams to ensure alignment in the adoption of Data Mesh principles and self-serve platform capabilities.

Mentorship: Provide guidance and mentorship to team members, ensuring a consistent understanding of Data Mesh methodologies and fostering a collaborative learning culture.

Self-serve Platform Promotion: Advocate for and guide the use of the organization's self-serve data platform, ensuring that domain teams are fully equipped to manage their data pipelines, products, and governance responsibilities.

Change Management: Assist in change management efforts as the organization adopts Data Mesh, providing thought leadership and troubleshooting to overcome adoption challenges.

Required Qualifications:

5+ years of experience in data analytics, data product development, or data engineering, with a strong focus on delivering impactful business insights through data visualizations and dashboards.

2+ years of experience in leading or guiding teams in developing data products, particularly analytics and visualization-driven products, focusing on data storytelling and decision-making support.

Deep understanding of data product lifecycle, including data sourcing, data transformation, and delivering analytics-driven insights using tools like Power BI, Tableau, or similar visualization platforms.

Strong understanding of Data Mesh principles, with practical experience in data-as-a-product thinking, decentralized ownership, and self-serve data analytics platforms.

Experience with cloud-based data platforms (AWS, GCP, Azure), data pipelines, and visualization frameworks that allow for scalable and maintainable data products.

Proficiency in modern data visualization and business intelligence tools (e.g., Tableau, Power BI, Looker), with hands-on experience in creating impactful, user-centric visualizations.

Strong communication and mentoring skills, with the ability to translate complex data analytics concepts to non-technical team members and stakeholders.

Proven adaptability in collaborating with domain teams across varied business functions, helping them develop and deliver their own data products and insights.

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