TLG manages the Marketplace ecosystem: connecting catalogs, pricing, inventory, and orders between SFCC/internal systems and dozens of third-party marketplaces (Zalando, Miinto, Nordstrom, Amazon, Mirakl, Farfetch, and others), with production deployments running on Kubernetes.
The tlg-mkt repository is a multi-submodule monorepo (Bitbucket) containing shared libraries, platform services, database connectors, and one submodule per marketplace (mktps/mkt-marketplace-). Each integration exposes microservices and jobs (catalog connector, order connector, feed export, Kafka consumers, cron jobs).
What you'll do:
Develop and maintain marketplace connectors (catalog, inventory, orders, RMA, feed export) in Python, leveraging the core shared libraries.
Extend the product connector and ingestion/feed export flows (JSONata mapping, feed caching, batch jobs, metrics).
Collaborate on PostgreSQL migrations (Alembic in mkt-marketplace-db) and brand/channel-specific configurations.
Integrate and troubleshoot event-driven workflows (Kafka, consumer groups, KEDA on Kubernetes clusters).
Contribute to data quality and parity initiatives (comparison of enrichment strategies, feed equivalence, coverage/diff reporting) as required by the product roadmap.
Write tests (pytest), comply with type checking (basedpyright), and follow the team's branching and release model.
Support deployments and troubleshooting across development, staging, and production environments (Helm, environments, secrets, logs).
What we're looking for:
3+ years (Mid-level) or 5+ years (Senior-level) experience developing Python backend applications in production environments.
Solid understanding of distributed systems concepts (idempotency, retries, dead-letter queues, backpressure).
Ability to navigate large legacy codebases, ADRs/internal documentation, and effectively reduce scope (targeted fixes, no over-engineering).
Clear communication skills in Italian and/or English when collaborating with Product, Operations, and other developers on marketplace integrations.
Ability to independently set up a local development environment: Poetry, PostgreSQL in Docker, Git submodules, .env configuration, and integration testing.
Technical Stack (Must-Have):
Python 3.11+
Poetry, Poe (task runner), pytest
FastAPI / Starlette (where applicable), microservices architecture patterns
PostgreSQL, SQLAlchemy, Alembic migrations
Apache Kafka (producer/consumer patterns, schema evolution)
JSONata (feed export and catalog mapping)
Kubernetes, Helm (mktp-base-chart), KEDA, Docker
Bitbucket Pipelines, Azure Artifacts (private PyPI repository)
basedpyright, Black/Ruff repository conventions
Nice to have:
Experience with B2B2C e-commerce, marketplaces, or PIM/product catalog systems (variants, price books, inventory).
Knowledge of Salesforce Commerce Cloud (SFCC), SCAPI, or OCAPI (orders, catalog management).
Familiarity with Mirakl or similar marketplace APIs.
Experience working with monorepos, Git submodules, and multi-repository release processes.
TypeScript and edge workers (e.g., Cloudflare) if the team expands ingestion pipelines alongside the Python core.
Experience with observability tools (Prometheus, Pushgateway) and cloud operations (AWS/Azure — depending on team alignment).
What you'll find in the project (real examples)
20+ marketplace integrations under mktps/, each with dedicated connectors.
Shared libraries: mkt-marketplace-core-lib, products-core, orders-core, mirakl-lib, test-core.
Platform components: APIs, admin tools, monitoring, centralized database, and shared Helm deployments.
Typical work includes: launching a new marketplace channel, fixing feed exports, building file/API ingestion jobs, maintaining order consumers, tuning batch processes, and configuring databases for specific brands (e.g., LN-CC, Cavalli, etc. — subject to confirmation with the team).
Current Initiative (example)
Comparative analysis of catalog enrichment strategies (V1 shopper vs. V2 admin_primary), including side-by-side PostgreSQL schemas, payload canonicalization, and feed-critical parity reporting. This is particularly relevant for candidates with a strong interest in data quality, catalog pipelines, and product data governance.
What we offer:
Benefits: monthly lunch tickets, discounts to our owned brands and brand partners, and additional perks in the form of local discounts and offers.
Learning Development: continuous learning experience with TLG University and other projects.
Workplace People: be part of the young (31 on avg.) and international (30+ nationalities) #TLGpeople group and work in a dynamic and fast-moving environment.
