QA Automation Lead/Project Manager

Position - QA Automation Lead/Project Manager

Location - Raritan, New Jersey

Duration - Full-time

Key responsibilities

Delivery and planning

• Own the end-to-end delivery plan across 3–6 concurrent workstreams, from initiation and scoping through build, test, release and hypercare.
• Run delivery across the full SDLC in Agile (Scrum/Kanban), waterfall or hybrid models, choosing the right approach per workstream.
• Build and maintain an integrated plan with milestones, critical path and cross-team dependencies (for example, a data pipeline that must land before a model can be trained or a dashboard released).
• Run sprint ceremonies or delivery cadences with team leads; keep backlogs groomed and ready.

Scope, risk and governance

• Maintain the RAID log (risks, assumptions, issues, dependencies) and escalate early with options, not just problems.
• Control scope through a clear change process; quantify impact on timeline, cost and quality before changes are accepted.
• Track budget and resource use, including cloud and Databricks consumption against forecast, with the platform lead.
• Ensure release readiness: test sign-off, security and data governance checks, deployment and rollback plans.

Stakeholders and communication

• Be the single point of accountability for delivery status to sponsors and business owners.
• Produce weekly status reports and monthly steering committee packs with RAG status, decisions needed and trade-offs.
• Translate technical constraints into business impact, and business priorities into clear asks for engineering.
• Coordinate with vendors and partners where work is outsourced.

Team and continuous improvement

• Remove blockers and resolve cross-team conflicts on priority and capacity.
• Run retrospectives and post-release reviews; turn lessons into changes in process.
• Maintain delivery tooling (Jira/Azure DevOps, Confluence) as the source of truth.

Must-have qualifications

• 6 years managing IT or software projects, with at least 3 years running multiple workstreams or a programme at the same time.
• Strong command of the SDLC: requirements, design, build, test (unit, integration, UAT), release and support.
• Hands-on experience with Agile delivery and hybrid models; able to plan to fixed milestones while teams work in sprints.
• Proven dependency and critical-path management across engineering teams that do not report to you.
• Track record of delivering to time and budget, with examples you can quantify (team size, budget, timeline, outcome).
• Clear written and verbal communication with both engineers and senior business stakeholders, including steering committee reporting.
• Proficiency with Jira or Azure DevOps, Confluence, and MS Project or Smartsheet.
• Bachelor’s degree in Computer Science, Engineering, Business or equivalent experience.
• PMP, PRINCE2, PMI-ACP, CSM or SAFe certification preferred.

Nice-to-have technical knowledge

You do not need to build on these platforms. You need enough working knowledge to plan realistically, ask the right questions and spot risk early.

Area

Expected level

What that looks like in practice

Databricks

Working knowledge (important)

Understands workspaces, notebooks, jobs/workflows, Delta Lake, Unity Catalog and the medallion (bronze/silver/gold) pattern; knows how cluster and job costs accrue; can follow a pipeline design discussion

AWS

Basic

Familiar with core services (S3, IAM, EC2, VPC, Lambda) and how environments (dev/test/prod) are set up; understands why access, networking and security reviews take lead time

AI / ML

Basic

Understands the model lifecycle (data prep, training, evaluation, deployment, monitoring), MLflow, and GenAI concepts such as LLMs, RAG and prompt evaluation; knows why AI work needs time for experimentation and data quality

Product development

Basic

• Has worked alongside product managers on roadmaps, MVP scoping, user stories and acceptance criteria; can tell a scope change from a refinement