Description review

Senior Engineering Manager

CData Software · United States · back to the listing

HR standards

55/100

needs work

Title ↔ description

94/100

strong

Reads as

Engineering Manager

100% confident

What this role officially is

software manager — ESCO, the EU occupation classification

Software managers oversee the acquisition and development of software systems in order to provide support to all organisational units. They also monitor the results and quality of the different software solutions and projects implemented in the organisation.

Also known as: applications manager, software managers, ICT applications manager, software applications manager, soft manager

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What the listing never says

  • 49 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

About CData Software, Inc.

CData is the data layer between AI and ROI—delivering the connectivity, context, and control that make enterprise AI more accurate. One platform for live access and data replication across 350+ sources, semantic intelligence that ensures context-aware responses, and built-in governance for every AI-to-data interaction. Powering AI and analytics workloads for Anthropic, Databricks, Microsoft, Google, Palantir, and more than 10,000 customers worldwide.

Behind that impact is a global team of passionate problem-solvers, engineers, and innovators who are redefining what’s possible in data connectivity.

Headquartered in Chapel Hill, North Carolina, CData has over 500 team members, with offices in North America, Europe, and Asia. We take pride not just in what we build, but in how we build it: together, with curiosity, creativity, and a shared drive to push boundaries.

SeniorEngineering Manager

Job Summary

Lead engineering teamsbuildingAI-powered data connectivitysolutionsonCDataConnect AI.In this role, you will combine strongpeopleleadership, technical judgment, and execution to help engineering teamsdeliver high-quality software quickly and effectively.

Asa SeniorEngineering Manager, you willprovide leadership to engineering teams, owning execution and delivery while helpingestablishthe operating practices, technical direction, and organizational clarity needed for teams to perform effectively. You will ensureprioritiesareclear, work moves forward, dependencies and blockers are addressed, and commitmentsremainon track while partnering with Engineering and Product leadership on capacity, priorities, risks, and longer-term planning.

You will also help foster a shift-left engineering model in which engineers engage earlier in discovery and solution definition. Rather than simply executing against fully prescribed requirements, engineers will partner with Product and other stakeholders to understand customer and business problems, shape technical solutions, and translate those solutions into actionable technical work. AI is used throughout the process, both in the product we ship and in how we build it, to support solution exploration, planning, and development without loweringthetechnical qualitybar.

You will balance this execution with strongpeopleleadership, developing engineers through regular feedback, coaching, career development, and clear performance expectations. You will create an environment of accountability, autonomy, collaboration, and continuous learning while ensuringthe engineeringteam's workremainsaligned with broaderProduct andEngineering priorities.

Location(s):Remote, U.S. / North Carolina Research Triangle or East Coast (preferred)

Eligibility: Applicants must be US-based and legally authorized to work in the United States without the need for employer sponsorship, now or in the future.

Key Duties & Responsibilities:

Responsibilities include but are not limited to:

People Leadership

• Lead and develop engineering teams, providing regular coaching, feedback, and performance management while fostering a culture of accountabilityand innovation.

• Developseniorengineers,technical owners, and emerging leaders, increasing the leadership capacity within the organization.

• Empower senior engineers and technical ownersto take ownership of initiatives, rapidly prototype andvalidatesolutions, make sound technical decisions, and drive work from discovery through implementation.

• Hire, onboard,retain,anddevelopstrong engineering talent whileidentifyingcapability gaps and partnering with Engineering leadership on organizational and workforce needs.

• Partner with Engineering leadership on team structure, capacity planning, resource allocation, and talent development across the organization.

Execution and Delivery

• Own execution and deliveryacross assigned engineering teams or a broader engineering area,ensuring priorities, ownership, dependencies, risks, and commitments are clearly understood and actively managed.

• Continuously improve operating practices that enable predictable delivery,appropriate accountability, and visibility across teams without creating unnecessary process overhead.

• Ensure effective team-level operatingrhythms, including planning, backlog readiness, delivery tracking, and blocker resolution, while developing leaders within teams who can increasingly drive day-to-day execution.

• Identifyand resolve cross-team dependencies and systemicdelivery issues, partnering with other Engineering leaders and Product leaders when challenges extend beyond the immediate team.

• Use streamlined workflows, automated reporting, and meaningful engineering and delivery metrics toidentifytrends, improve execution, and inform decisions.

• Communicate progress, risks, challenges, resource needs, and delivery outcomes clearly and proactively to Engineering leadership and other stakeholders.

Technical Leadership

• Providestrongtechnical leadership and judgmentacross teams,ensuring engineering decisions align witharchitectural direction, quality expectations,reliability standards,andbroader technical strategy.

• Partner closely with senior and principal-level engineers to evaluate technical approaches, challenge assumptions, and ensureappropriate ownershipof architecture and technical decision-making.

• Stay technically credible bymaintainingenough hands-on technical engagement to effectively guide the teamand make informedtechnical decisions.

• Identifyrecurring technical challenges across teams and help drive broader improvements to engineering practices, architecture, tooling, and ways of working.

Operational Ownership

• Ensure effective operational ownership across assigned teams, including sustainable on-call practices,appropriatestaffing, and clear accountability for production systems.

• Ensure teams establish and effectively use SLOs, error budgets, and other reliability measures and take action when trends move in the wrong direction.

• Provide leadership during major incidents, ensuring effective coordination, decision-making, escalation, and stakeholder communication through resolution.

• Driveoperational excellenceacross teams throughleading effective postmortems and ensuringmeaningful action items are trackedthrough closure.

• Identifyrecurring operational patterns andpartneracross Engineering to address root causes and improve reliability at an organizational level.

Discovery & AI-Assisted Development

• Partner closely with Product and cross-functional stakeholders to ensure teams have clear problem statements, business context, priorities, and success criteria while preservingappropriate engineeringownership of solution design and implementation.

• Championeffective use of AI-assisted development practices,helping teamsleverageAI appropriately for solution exploration, technical planning, ticket creation, development, and other workflows whilemaintainingengineering quality and accountability.

• Helpestablisheffective Product and Engineering working practices across teams, resolving areas of unclear ownership or ineffective handoffs.

• Enableengineers toparticipateearlier in discovery, clarify problem statements, contribute to requirements, develop technical solutions, and translate those solutions into well-defined technical work.

• Identifyopportunitiesto use AI, automation, and improved engineering practices to increase developer productivity and organizational effectiveness.

Qualifications

Must Haves:

• 8+ years of software engineering experience, including hands-on experience in enterprise or SaaS environments with a strong focus on technical competency and innovation.

• 4+ years of engineering managementand/or people managementexperience withdemonstratedsuccess leading, coaching, and developing engineering teams.

• Experience leading multiple engineering teams or initiatives spanning multiple engineering teams and stakeholders.

• Proven ownership of team execution and delivery, including planning, prioritization, dependency management, riskidentification, and continuous improvement of development workflows.

• Experience partnering with senior Engineering and Product leadership on organizational priorities, resource needs, technical tradeoffs, and execution strategy.

• Experience owning production services, including on-call, SLOs, incident response, and postmortems.

• Experience working in highly collaborative Product and Engineering environments where engineersparticipateactively in discovery, requirements definition, technical solutioning, and delivery.

• Strong technical judgment with the ability to guide design decisions, challenge assumptions, and empower senior and lead engineers to own technical initiatives.

• Strong communicationand stakeholder management skills, with the ability to create clarity across engineering, product, and other cross-functional teams.

• Experience with cloud platform management and architecture, preferably Azure, supporting scalable, high-performance systems and cloud-native deployments.

• Strong Java/Kotlin development experience, with the ability toprovidetechnical guidance across backend services and microservices development.

• Experience leveraging or leading teams thatleverageAI-assisted software development tools and workflows.

• Recent hands-on coding experience ispreferred.

• Kubernetesexperience and familiarity with container orchestration and deployment is a plus.

• React framework experience is a plus.

• Experience designing and implementing microservice architectures supporting distributed systems and system reliability is a plus.

• Bachelor's degree inComputerScience, Engineering, or a related field, or equivalent practical experience.

Travel Required:Travel is not required for this role.

US Only: The typical base pay range for this role across the US is $190,000-$225,000 per year. The actual range may vary depending on specific locations.

Data Access & Compliance: This role may access, process, or support systems containing confidential customer data, including PII, PHI/ePHI, and other regulated or sensitive information. The employee must comply with CData’s Information Classification and Management Policy, HIPAA-related safeguards where applicable, access-control requirements, data-handling procedures, and incident-reporting obligations.

Benefits & Perks / What you’ll Get:

• As part of our comprehensive benefits offerings, we provide Medical, Dental, and Vision plans with company-paid insurance premiums

• HealthSavingAccountoffering with company contributionto help mitigate increasing health costs

• FlexibleSavingsAccountand Dependent Care FSA

• Generous20-dayPTO and11paid holidays

• 401k with 100% company match up to 6% of contribution

• A remote-friendly, high-trust culture that empowers collaboration, celebrates curiosity, and encourages innovation

• Work closely with your manager to define professional development and learning opportunitiesthat match your career goals

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 63 before penalties). Reviewed 21 Sep 2026.