Senior Data Engineer (AI, GenAI)

TL;DR

Senior Data Engineer (AI, GenAI): Design, build, and optimize modern cloud-based data platforms powering analytics, AI, and data products with an accent on scalable batch, streaming, and near-real-time pipelines. Focus on enabling production-grade AI/GenAI data workflows (including RAG and agent-based systems), while ensuring governance, security, observability, and cost-efficient data serving.

Location: Sofia

Company

hirify.global is an experience innovation company that helps brands unlock value by blending data, AI, creativity, and technology.

What you will do

• Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric primary, plus AWS/GCP, Databricks, Snowflake).
• Build reliable batch, streaming, and near-real-time ingestion, transformation, and curation workflows for structured and unstructured data.
• Deliver model-ready datasets for analytics, machine learning, causal modeling, and optimization systems, including GenAI pipelines (LLMs, RAG, vector-based flows).
• Model data for analytical and operational use cases and orchestrate end-to-end workflows using tools such as Airflow, dbt, Lakeflow (or equivalents).
• Apply governance, lineage, quality, and access control (RBAC/ABAC) and establish data observability (freshness, reliability, SLA adherence).
• Enable data serving layers (APIs, feature inputs, analytical endpoints) and continuously optimize performance, scalability, and cost efficiency.

Requirements

• Strong hands-on experience with Apache Spark and Delta Lake, plus strong programming skills in Python and SQL.
• Proven experience building batch and streaming data pipelines and production-grade data platforms, including data modeling, quality, and governance.
• Experience with major cloud platforms; preference for Microsoft Azure/Fabric, with AWS or GCP experience expected.
• Experience with lakehouse architectures and distributed data systems, with strong scalability, reliability, and performance understanding.
• Strong problem-solving skills focused on scalability and reliability, with a collaborative approach in cross-functional teams.

Nice to have

• Experience with GenAI and AI data systems (e.g., RAG pipelines, vector databases, LLM data preparation).
• CI/CD for data pipelines and infrastructure-as-code tools such as Terraform, ARM, or CloudFormation.
• Exposure to Kafka/streaming technologies, Spark optimization, and advanced analytics/ML workloads (including causal or experimentation platforms).

Culture & Benefits

• Hybrid work options and 25 vacation days.
• Co-subsidized transportation and Multisport cards.
• Premium health insurance.
• Training policy for technical and certification-related events, courses, and credentials.
• Self-care program with psychological consultations for you and the team.
• Cozy office space, plus team events and company gatherings.

Hiring process

• Talent Acquisition reviews the application; CV should cover relevant experience and expertise.
• Interviews evaluate skills, experience, and potential; no need to provide age, gender, marital status, or a headshot.
• Reasonable accommodations are available during the interview process if requested.