What you’ll do
- Lead discovery workshops with clients to understand business goals, technical constraints, data maturity, and AI opportunities.
- Design end-to-end data and AI architectures across cloud, lakehouse, warehouse, analytics, ML, and GenAI use cases.
- Define solution blueprints using platforms such as Databricks, Microsoft Fabric, Azure, AWS, GCP, Snowflake, Delta Lake, and related technologies.
- Translate business requirements into technical roadmaps, architecture diagrams, delivery estimates, and implementation plans.
- Identify where AI, machine learning, LLMs, RAG, vector search, automation, or analytics can create measurable business value.
- Guide teams in building scalable data pipelines, governed data platforms, AI applications, and reusable engineering frameworks.
- Support pre-sales activities by contributing to proposals, solution narratives, technical estimations, client presentations, and proof-of-concept plans.
- Define best practices for data modeling, medallion architecture, SCD/CDC, metadata-driven engineering, data quality, governance, security, and observability.
- Collaborate with engineering teams during delivery to ensure that architecture decisions are implemented correctly and sustainably.
- Review technical designs, mentor engineers, and help raise delivery standards across the Data & AI practice.
- Stay informed about advancements in cloud, Databricks, Microsoft Fabric, GenAI, LLMs, vector databases, and AI engineering practices.
What we are looking for
- 6+ years of experience in data engineering, software engineering, cloud architecture, AI engineering, or a related technical field.
- Strong experience designing and delivering enterprise data platforms, lakehouses, warehouses, analytics platforms, or AI-enabled solutions.
- Hands-on experience with Azure, Databricks, Delta Lake, PySpark, SQL, Python, and modern data orchestration tools.
- Strong understanding of data modeling concepts, including dimensional modeling, Data Vault, medallion architecture, SCD Type 1/2, CDC, schema evolution, and metadata-driven pipelines.
- Experience with cloud-native solution design, including security, scalability, cost optimization, monitoring, CI/CD, and operational readiness.
- Practical understanding of AI and GenAI solution patterns, including LLMs, embeddings, vector databases, RAG, prompt engineering, model evaluation, and AI application integration.
- Ability to estimate technical work, define delivery phases, identify risks, and communicate trade-offs clearly.
- Strong client-facing communication skills and the ability to explain technical concepts to business stakeholders.
- Experience mentoring engineers and guiding technical delivery across multiple workstreams.
- Strong ownership mindset, structured thinking, and the ability to operate confidently in ambiguous client environments.
Nice to have
- Experience with Microsoft Fabric, Snowflake, Unity Catalog, Purview, dbt, Airflow, MLflow, or DataOps tools.
- Experience with LangChain, LangGraph, CrewAI, Semantic Kernel, OpenAI, Hugging Face, Chroma, Qdrant, Milvus, Pinecone, or similar AI and vector search technologies.
- Experience designing architectures for regulated industries such as finance, energy, manufacturing, healthcare, or enterprise software.
- Experience in consulting, pre-sales, technical discovery, or proposal development.
- Cloud, Databricks, Microsoft Fabric, Snowflake, architecture, or AI-related certifications.
- Experience building proof-of-concepts that later evolved into production systems.
What we offer
- A senior role with direct influence over Magix AI’s Data & AI practice.
- Opportunity to shape complex international projects from strategy to production.
- Exposure to modern data, cloud, and AI technologies.
- A collaborative team of experienced engineers, architects, and AI specialists.
- Support for certifications, learning, conferences, and professional growth.
- Hybrid or remote work model, private health insurance, and competitive benefits.