Senior Physical Design - Partition Lead

Capgemini Engineering; Wrocław; Hybrid; PLN 320,000 - 520,000; Full time

Benefits offered by this job

Medicover medical care

Private life insurance

Sports card

Capgemini Helpline for wellbeing

Hybrid work model

Home office package

Job summary

Capgemini Polska is seeking a Physical Design Partitioning Lead to drive high-complexity PD activities for advanced nodes (10nm and below). The role involves leadership in partitioning, floorplanning, timing, power mesh and clock tree planning, with responsibilities spanning ECOs, sign-off and multi-cycle delivery.

The ideal candidate will have deep PD experience, scripting ability (Perl/TCL/Python), and a track record of mentoring small teams.

Qualifications

• Experience in Physical Design at 10nm and below
• Strong leadership or mentoring experience
• Proficiency in scripting and design automation tools

Responsibilities

• Lead or contribute to PD in full chip or block-level designs at advanced nodes
• Perform floorplanning, partitioning/budgeting, power mesh distribution, clock tree planning and analysis
• Manage timing analysis, ECO tasks, SI/noise considerations and sign-off
• Oversee validation/qualification tasks: Formal Verification, EM/IR, DRC, LVS, Antenna, ERC
• Contribute to low-power solution development and timing-related scripting
• Develop/enhance timing scripts for clock skew analysis and path analysis
• Complete multiple design cycles with minimal supervision; may lead PD engineers

Skills

Synthesis flow

DFT scan/coverage

Floorplanning

Power planning

CTS/Place & Route

Timing closure

Scripting Perl/TCL/Python

Makefile

Timing STA/PTSI

EM/IR/DRC/LVS/ERC analysis

Sign-off tape-out closure

Partitioning

Lead a small team

Tools

Makefile

Job description

Capgemini Polska is seeking a Physical Design Partitioning Lead to drive high-complexity PD activities for advanced nodes (10nm and below). The role involves leadership in partitioning, floorplanning, timing, power mesh and clock tree planning, with responsibilities spanning ECOs, sign-off and multi-cycle delivery.

The ideal candidate will have deep PD experience, scripting ability (Perl/TCL/Python), and a track record of mentoring small teams.