[Hiring] Enterprise Migrations Practice Area Lead @Infinite Lambda

Role Description

Every enterprise wants to be AI-ready, and most are held back by legacy data estates built over decades. As Enterprise Migrations Practice Area Lead, you’ll own how Infinite Lambda solves that problem: moving the world’s largest organisations off Informatica, Talend, SSIS/SQL Server, DataStage, stored procedures and, increasingly, SAS and Alteryx, onto modern platforms ready for AI.

Enterprise migrations are a core pillar of our growth strategy, and this role sets the standard for how we deliver them globally. The practice spans the full migration lifecycle:

• Assess: Estate discovery, feasibility analysis and migration strategy, ending in a fixed-cost, fixed-timeline proposal that gives clients certainty from day one.
• Convert: Automated code conversion with Flowline, our proprietary product, which combines deterministic and LLM-assisted methods. This stage also covers refactoring, optimisation and a first-pass ontology that lays the foundation for AI use cases.
• Validate: Reconciliation architecture and row-level sign-off, so every migration is provably correct.

The first part is delivery excellence that compounds . You’ll make sure every migration we deliver is better than the last. That means defining the standards, building the playbooks and reusable assets, and turning the lessons from each strategic engagement into capability across the practice. You’ll also develop the engineers and leads who carry that standard across AMER, EMEA and APAC.

The second part is commercial impact . You’ll turn delivery quality into a competitive edge: faster delivery, sharper scoping and pricing, and healthy margins you can measure and report on. Working closely with Sales and Solution Engineering, you’ll shape the offer that makes Infinite Lambda the obvious choice for enterprise migration, anywhere in the world.

Responsibilities

• Practice and standards:
  • Be the person engineers, sales and clients ask when a migration question is hard: what to migrate first, what to refactor and what to move as is, and how to resolve conflicting logic.
  • Own the migration standard for Assess, Convert and Validate. This covers reference architectures, sequencing, reconciliation and stage-gate checklists, and what we won’t do.
  • Make sure Fast and Deep Discovery produce a defensible estimate, a dependency map and early red flags before we commit to a fixed price.
  • Hold the same quality bar in every region: conversion quality, reconciliation sign-off and post-go-live incidents.
  • Keep the practice up to date as Flowline, the source parsers and the target platforms change (Snowflake, Databricks, BigQuery, Iceberg).
• Knowledge, IP and the asset catalogue:
  • Join engagements at scoping and agree what each strategic migration should leave behind (patterns, decisions, failure modes, measurements) and who will capture it.
  • Capture lessons at wave checkpoints, and close each engagement with a review of what worked, what didn’t, and what should change in the standard.
  • Decide which lessons become reusable assets and which stay one-offs.
  • Bring field requirements and recurring challenges to the Flowline product team, and move proven assets into Product & Services.
• People and enablement:
  • Build a global bench of migration specialists.
  • Develop engineers across AMER, EMEA and APAC into a team that can deliver migration waves to our standard, independently and at scale.
  • Own the path from practitioner to leader.
  • Design and run the progression that takes engineers from dbt and Snowflake foundations, through Flowline accreditation and deep expertise in a legacy source system, to owning delivery waves and ultimately leading client assessments.
  • Turn what we know into how we work.
  • Make our accelerators and existing assets visible and reusable across every team, so each engagement starts from our best work rather than a blank page.
• Commercial:
  • Make sure live engagements actually use the practice’s accelerators.
  • Help Sales and Sales Engineers scope, estimate and price from measured delivery speed, so the client pays for the acceleration instead of getting it for free.
  • Make the commercial case for the practice in proposals, extensions and new scope. This includes turning Discovery engagements into migrations and expanding into BI and semantic-layer work.
• Partners and internal work:
  • Act as the technical lead in joint pursuits with Snowflake, Databricks, dbt and Fivetran, and feed what we learn in delivery into joint go-to-market, certifications and co-marketing.
  • Write interview material and run technical interviews for migration roles.
  • Present the practice’s work inside the company and, where it makes sense, at external events and in case studies.

Requirements

• Ownership at a strategic level: You take full accountability for outcomes, not just tasks. You’ve owned a practice, a service line or a major programme end to end (its direction, quality, people and commercial results), and you’re comfortable making the calls that shape how a business delivers.
• Enterprise migration experience at scale: You have a track record of leading large, complex migrations off legacy platforms such as Informatica, Talend, Oracle, SSIS or DataStage, and you know where these programmes tend to go wrong.
• Depth across both ends of the migration: You have hands-on knowledge of legacy source systems and modern platforms (Snowflake, Databricks, BigQuery, Iceberg, dbt, Fivetran), plus a structured approach to assessment, conversion and validation.
• A builder of repeatable delivery: You’ve defined reference architectures, sequencing frameworks and quality gates, and built libraries of reusable assets and accelerators that teams actually use.
• A multiplier of talent: You’ve developed engineering teams across regions through mentoring, structured skill pathways and accreditation, and you’ve raised the bar for how those teams deliver.
• Credibility with clients and partners: You can lead discovery sessions with senior client stakeholders, act as the technical lead in joint pursuits with partners such as Snowflake and Databricks, and assess engineering talent in interviews.
• Commercial awareness: You understand how delivery choices affect scoping, pricing and margin, and you enjoy working with Sales to win the right work.

Benefits

• We support your growth with dedicated learning time, access to top-notch resources and a knowledge-sharing culture.
• You work autonomously here in a wholesome environment and get as much paid holiday as you need.
• The projects are diverse and give you plenty of opportunity to experiment with new tech.
• The benefits are plenty, with work-from-home budget, a company MacBook and more on the list.

Company Description

Infinite Lambda is an equal opportunity employer. Our inclusive culture celebrates diversity and treats everyone with dignity and respect. Accordingly, our selection process will never discriminate against applicants on the grounds of any characteristics, such as disability, age, gender, sexual orientation, family status, race, faith or other.