Sviat Nahirnyi

Forward Deployed Engineer, building data platforms since 2020. I embed with the people who run operations — in warehouses, factories and client offices — map how the work really happens, and ship the Data & AI platforms they end up relying on: Lakehouses, real-time streaming, RAG and LLM evaluation. Co-founded Graphit and grew its Data & AI practice from zero to 17 engineers across 9 client engagements.

• 0 → 17engineersGrew the Data & AI practice across 9 client engagementsGraphit
• −30%flagged chatbot responsesLLM-as-a-Judge evaluation platformGraphit
• +6%operational performanceEmbedded on-site in a logistics client’s warehousesGraphit
• 39 → 1sources into one LakehouseServing 5 analytics & ML teamsSigma Software
• −37%pipeline runtimeIncremental PySpark on DatabricksSigma Software
• 50K+events / secondSpark Structured Streaming for telecomSoftServe

1. Co-Founder & Lead, Data & AI Platforms· at Graphit (now Datasoft Group)

   Mar 2023 – Aug 2026London, UK

   Co-founded a London data & AI consultancy and built its Data & AI practice from zero — selling, designing and shipping platforms on-site with clients.

   • Closed the company’s largest enterprise deal — a top-20 European logistics company — by leading the pitch and end-to-end solution design.
   • Embedded on-site at the client’s warehouses to map operational workflows, then delivered analytical data platform solutions that improved operational performance by 6%.
   • Worked forward-deployed at Dow Jones’ Barcelona office on vector database scalability for production retrieval workloads.
   • Grew the Data & AI practice from zero to 17 engineers across 9 client engagements — real-time platforms, Lakehouse migrations, LLM evaluation systems.
   • Cut flagged chatbot responses by 30% by architecting an LLM-as-a-Judge evaluation platform.

   Stack: LLM-as-a-Judge · Vector retrieval · Lakehouse migrations · Real-time platforms · Presales · Solution design

2. Senior Data Engineer· at Sigma Software Group

   Jul 2023 – Jan 2025Münster, Germany

   • Delivered the source-of-truth Lakehouse for an international logistics company — 39 operational sources consolidated into one platform serving 5 analytics and ML teams — by embedding on-site at the client’s factory to design ETL flows with operations staff.
   • Designed analytical dashboards for factory and logistics stakeholders on-site, mapping shop-floor workflows directly into data models and reporting.
   • Reduced end-to-end pipeline runtime by 37% by building incremental PySpark pipelines on Databricks.

   Stack: Databricks · PySpark · Lakehouse · ETL · Dashboards

3. Presales Software Engineer· at GreenM

   May 2023 – Aug 2023Hybrid, US

   • Won a data-platform tender for an aerospace company via a one-month PoC delivered directly with the client’s stakeholders, validating ingestion, storage, and query latency on terabytes/day.
   • Enabled unified alerting across 7 networking-metric sources by building the Kubernetes-native ingestion layer for a Cisco observability PoC.

   Stack: Kubernetes · PoC delivery · Observability · TB/day ingestion

4. Data Engineer· at Netminds

   Sep 2022 – May 2023Remote

   • Halved new-pipeline delivery time (4 days → 2) by rebuilding the platform around reusable ingestion templates.
   • Lifted loyalty engagement 10% with Spark / Scala pipelines feeding an AI-driven offers engine.
   • Shortened release cycles from 3 days to 1 by establishing Azure DevOps CI/CD for Databricks.

   Stack: Spark · Scala · Databricks · Azure DevOps

5. Big Data Developer· at SoftServe

   Sep 2021 – Sep 2022Remote

   • Built a Spark Structured Streaming system handling 50K+ events/second for real-time telecom network-map visualisation and latency detection.
   • Translated ambiguous stakeholder requirements into service boundaries, SLAs, and data contracts; built demos used in design reviews that helped upsell the account.

   Stack: Spark Structured Streaming · Real-time · Data contracts · SLAs

6. Data Engineer· at N-iX

   Oct 2020 – Sep 2021Remote

   • Secured sensitive datasets for a Fortune 500 company with a permissioned AWS data warehouse — Airflow, RBAC, Terraform CI/CD — plus a data-quality framework of 100+ automated checks.

   Stack: AWS · Airflow · Terraform · RBAC · Data quality

Forward Deployed

• On-site solution design
• Enterprise PoCs
• Requirements → data contracts
• Presales

AI / LLM

• HuggingFace
• LangChain
• LLM-as-a-Judge evaluation
• Vector retrieval
• RAG
• MLflow
• Agentic systems

Data & Streaming

• SQL
• Spark
• Streaming
• Databricks
• Airflow
• Kafka
• Python
• Scala
• Flink
• Snowflake

Cloud & DevOps

• AWS (SageMaker, Bedrock, Glue, EKS, S3)
• Azure (ADF, Synapse)
• MLOps
• Kubernetes
• Terraform

M.Sc. & B.Sc. in Artificial Intelligence — Lviv Polytechnic National University (LPNU)

• ConvoInsightsAI analytics · Side project → Graphit platform

  See where your chatbot fails — in every conversation.

  Started as a side project; it later became one of Graphit’s key platforms for its customers.

• FortiumiOS app · AI

  The program you already follow. Now it runs itself.

• ActiumApp · AI

  Turn self-help books into daily quests.

• HilkaOpen source · MCP

  Log how you think, not just what you decided.