Backend Data Engineer (PHP/Symfony)

Backend Data Engineer (PHP/Symfony) Growth Leads is a leading affiliate and lead generation company working within the iGaming and finance verticals. We build high-end websites with quality content that helps customers make an informed buying decision - driving relevant traffic through organic and paid search. Job summary We are hiring a Backend Data Engineer (PHP/Symfony) to take ownership of data flows, API architecture, and internal tooling, ensuring systems are performant, extensible, and built for long-term evolution across a growing data ecosystem. This role is centered on building the core data and API layer that powers the organization’s internal and external systems. It involves designing and implementing scalable ingestion pipelines, structured data models, and reliable backend services that transform raw, heterogeneous data into consistent, usable, and well-governed assets. Responsibilities Design and implement scalable data ingestion pipelines for a wide range of structured and unstructured data sources (APIs, files, databases, streams, third-party integrations, etc.) Build and maintain a canonical, extensible data model that supports long-term evolution, interoperability, and backward compatibility Ensure ingested data is normalized, validated, deduplicated, enriched, and stored in a structured and future-proof manner Architect systems that support schema evolution, data lineage, traceability, and auditability Develop stable, well-documented, versioned APIs for internal and external consumers Design APIs with strong guarantees around backward compatibility, reliability, and long-term maintainability Establish clear API versioning, deprecation, and migration strategies API usage tracking so we can measure requests per customer, domain, token and endpoint Implement automated data curation and enrichment workflows using modern techniques such as machine learning, entity resolution, classification, semantic matching, and anomaly detection Build confidence scoring and validation mechanisms to assess automated data quality and integrity Create human-in-the-loop workflows that allow manual review, correction, approval, and intervention where automation is insufficient Develop internal tooling and dashboards for data operations, moderation, verification, and quality control Ensure high standards for observability, monitoring, alerting, and operational reliability across ingestion and serving systems Optimize systems for scalability, performance, fault tolerance, and low-latency API access Collaborate closely with product, platform, and domain experts to evolve data models and workflows over time Define and enforce engineering best practices around testing, documentation, schema governance, and deployment processes Implement secure access controls, privacy protections, and compliance-aware handling of sensitive data Contribute to technical architecture decisions with a focus on maintainability, extensibility, and long-term platform evolution Requirements Strong PHP and Symfony experience Strong PostgreSQL and Doctrine experience Symfony Messenger, Scheduler, Redis experience Strong knowledge of databases, search systems, and data indexing strategies OpenAPI / Postman / SDK-friendly API design experience Experience building ETL/ELT or data platform systems Proficiency in programming languages like HTML, CSS, JavaScript, and PHP Familiarity with data modeling, schema registries, and metadata management Experience applying AI/ML techniques to data extraction, enrichment, classification, or quality assurance Experience with version control systems like Git Excellent communication and teamwork skills Ideal Candidate 5–8+ years PHP & PostgreSQL experience (~6–10 years backend/data engineering overall) Strong Symfony experience building scalable backend systems, APIs, and internal platforms Experience designing data ingestion pipelines and working with mapping, normalization, abstraction, and transformation of structured/unstructured data Solid knowledge of data modelling, schema design, indexing, and performance tuning Experience with ETL/ELT workflows, Redis, messaging systems, and scalable backend architecture Strong understanding of API versioning, reliability, and backward compatibility Comfortable working with data quality, validation, observability, and operational reliability systems Nice to have (bonus): Exposure to AI/ML for data enrichment, classification, entity resolution, or anomaly detection