Hi, I'mRafael Ignaulin

Senior Data & AI Engineer

Senior Data & AI Engineer @ Nike · Founder @ ISTech Production LLM agents, MCP servers and RAG, on billion-row data platforms.

Remote, 15+ countries· Nike · Inter&Co · PagSeguro· Georgia Tech OMSCS (in progress)· ISTech: US & Global Clients
Background

About Me

I'm a Senior Data & AI Engineer, building production LLM systems on the large-scale data platforms I work on, and the founder of ISTech, the consultancy my B2B contracts run through. I currently deliver for Nike and Inter&Co, with operations expanding into Oceania and Europe. At Nike I build production AI systems on top of the data platform: an LLM analytics agent that turns plain-English questions into SQL, and the MCP server that plugs internal analytics APIs into Cursor. I built both as sole engineer, and both run in production. Underneath them, I'm a major contributor to the session-level clickstream table behind Marketing and Digital Experience analytics, billions of rows on Databricks, Spark and Airflow. I work AI-native: Claude and Cursor are part of my daily toolchain, and I ship the systems that make that possible for others. I've worked remotely from 15+ countries across Europe, Oceania, and South America, collaborating daily with teams in India, Ireland, the US, Canada, and Australia, always aligned to my clients' hours.

Education

M.S. Computer Science (OMSCS)

Georgia Institute of Technology

Aug 2026 - Present

Bachelor in Computer Science

Unochapecó

2020 - 2023

Academic Honor Medal: highest grade in the graduating class (~100 students)

Languages

English: C2 (Professional Proficiency)

Portuguese: Native

Key Achievements

  • ✓Built a production LLM analytics agent at Nike as sole engineer (Claude Sonnet, Streamlit, MLflow) that turns plain-English questions into SQL
  • ✓Built Nike's analytics MCP server as sole engineer (FastMCP + FastAPI), exposing internal analytics APIs to Cursor with YAML-driven tool registration
  • ✓Cut Spark data reads 98% on a daily Nike job (multi-terabyte runs down to tens of GB) with partition and column pruning
  • ✓Automated Nike's A/B test reporting end to end with Airflow, from weeks of manual Excel work to a few hours
  • ✓Major contributor to the session-level clickstream table powering Nike's Marketing and Digital Experience analytics (billions of rows, Databricks/Spark/Airflow)
  • ✓Own end-to-end the client segmentation platform at Inter&Co, a digital bank with 45M+ customers
  • ✓Founded ISTech, a B2B data engineering consultancy delivering to US enterprise clients across 6+ timezones
Career

Professional Experience

Founder & Principal Data & AI Engineer

ISTech (Own Consultancy)

Remote, Global

Jan 2023 - Present

  • •Founded the B2B AI and data engineering consultancy all my contract work runs through, currently delivering for Nike and Inter&Co and spanning Data Warehouses, Data Lakes, and Lakehouses on AWS, Azure, Spark, Kafka, Airflow, and Terraform.
  • •Delivered from 15+ countries across Europe, South America, and Oceania while holding enterprise contracts, always aligned to client hours, collaborating daily with teams in India, Ireland, the US, Canada, and Australia across 6+ timezones.
  • •Expanding into Oceania and Europe, with a professional network across Ireland, US, Canada, India, and Australia.

Senior Data Engineer (Marketing & Digital Experience)

Nike (Contract via ISTech)

Portland, OR (Remote)

Jan 2024 - Present

  • •Cut Spark data reads 98% on a daily job (multi-terabyte runs down to tens of GB) through partition and column pruning, skipping billions of small-file events the job never used.
  • •Automated A/B test reporting end to end with Airflow, replacing weeks of manual Excel work with consistent, fully automated readouts in a few hours, so product teams iterate faster.
  • •Major contributor to the session-level clickstream table Marketing and Digital Experience analytics run on: billions of rows, hundreds of GB, millions of new rows added daily, built on Databricks/Spark with advanced SQL (grouping sets, cross joins, rolling lookback windows) and orchestrated with Airflow.
  • •Built an LLM analytics agent (Claude Sonnet, Streamlit, MLflow), a multi-thousand-line Python codebase that turns plain-English questions into SQL, with confidence scoring that flags low-confidence answers for review.
  • •Built a FastMCP/FastAPI server exposing a dozen-plus analytics tools to Cursor. New tools are a YAML file, not a code change.
  • •Contributed a dozen loader classes plus a shared helper class to the team's Databricks/Airflow job library, covering task orchestration, Delta load/validate, A/B testing and freshness checks.
  • •Debugged a large production analytics API, root-causing recurring production bugs, and built a sizable cache-validation test suite to catch cached-vs-fresh discrepancies.

Data Engineering Lead (Client Segmentation)

Inter&Co (Contract via ISTech)

Remote

Jan 2023 - Present

  • •Own end-to-end the data platform behind client segmentation for a digital bank with 45M+ customers.
  • •Built a 6-zone medallion lakehouse on S3 and Delta Lake, orchestrated by Airflow across EMR and Kubernetes, replacing ad hoc pipelines with one consistent, config-driven architecture.
  • •Designed CDC ingestion from the bank's operational database via Kafka/MSK and Debezium, plus a near-real-time update engine (Spark micro-batches on Kubernetes, with Kafka and DynamoDB integrations) that keeps segmentation current between batch cycles.
  • •Built a reusable data-quality framework (document validation, composable rule chaining, structured error logging) adopted across every ingestion pipeline on the platform.
  • •Extended the platform to the bank's US operation (Delta current-plus-history tables, Kafka and DynamoDB publishing).
  • •Designed the platform's core segmentation logic and set the engineering standards (testing, CI/CD, error alerting) the team's 8 repositories now follow.
  • •Progressed Mid-Level → Senior → Lead across the engagement, growing from delivering pipelines to owning the platform and its engineering standards.

Data Engineer (Junior → Mid-Level)

PagSeguro / PagBank (via Compass.uol)

Remote

Apr 2021 - Oct 2024

  • •Designed and tuned an Amazon Redshift Data Warehouse with star/snowflake schemas, optimizing queries across 20+ tables with billions of rows (distribution/sort keys, compression, EXPLAIN) for a 10x performance gain, enabling Power BI dashboards that cut report generation from hours to minutes.
  • •Promoted from Junior to Mid-Level Data Engineer; wound the role down in Oct 2024 as contract work through ISTech became the focus.
Portfolio

Featured Projects

A selection of impactful data engineering projects I've led and contributed to at Nike, Inter&Co, and other organizations.

US Enterprise Data Platform (ISTech)

ISTech

End-to-end data engineering engagement for a US enterprise client, architecting a Lakehouse on AWS with Spark, Kafka, Airflow, and Terraform. Delivered production infrastructure while operating across US, Brazilian, and Oceanian timezones simultaneously.

Impact: Production data platform in market; client operating across 3 timezones

SparkKafkaAirflowTerraformAWSDatabricks

Session-Level Clickstream Table

Nike

Major contributor to a session-grain clickstream table rebuilt daily on Databricks/Spark, with billions of rows and millions added per day, using advanced Spark SQL (window functions, higher-order functions, pure-SQL funnel state machine). The single source of truth behind Marketing and Digital Experience dashboards, a production analytics API, and an LLM analytics agent.

Impact: One well-validated fact table powering every downstream analytics product

DatabricksSparkDelta LakeAirflowSQL

A/B Test Automation Platform

Nike

End-to-end automation for measuring multiple A/B tests with Airflow and Python, replacing weeks of manual measurement work.

Impact: Reporting from weeks of manual work to a few hours, fully automated and consistent

PythonSparkAirflowDatabricks

Multi-Terabyte Pipeline Optimization

Nike

Optimized a daily multi-terabyte Spark job through partition and column pruning, skipping billions of small-file events it never used.

Impact: 98% less data read per run: multi-terabyte down to tens of GB

SparkDatabricksPythonDelta Lake

LLM Analytics Agent

Nike

Production NL→SQL analytics agent on Claude Sonnet via Databricks Model Serving, with a Streamlit UI, conversation memory, MLflow tracing, and embedding-based confidence scoring against a curated ground-truth set so low-confidence answers get flagged for review.

Impact: Analysts self-serve analytics in plain English, with auditable confidence on every answer

PythonClaude SonnetStreamlitMLflowDatabricksLLM

Cloud Migration to Databricks

Nike

Moved the team's pipeline framework from EMR/Hive to Databricks (Delta Lake, Unity Catalog), reworking the jobs end to end.

Impact: Modern Lakehouse foundation for the analytics platform

DatabricksDelta LakeUnity CatalogAWS

Analytics MCP Server

Nike

FastMCP/FastAPI server exposing internal analytics APIs as tools inside Cursor, with YAML-driven dynamic tool registration: adding an endpoint is a config file, not a code change.

Impact: A dozen-plus analytics tools available to AI-assisted workflows, zero-code onboarding

MCP ServersFastMCPFastAPIPythonDatabricks

45M+ Customer Segmentation Platform

Inter&Co

End-to-end platform segmenting a digital bank's client base, built on a 6-zone medallion lakehouse on S3/Delta Lake.

Impact: Segmentation for a 45M+ customer base, batch + near-real-time

SparkDelta LakeKafkaAirflowKubernetesPython

Real-Time Segmentation Updates

Inter&Co

CDC ingestion from the bank's operational database (Kafka/MSK, Debezium, Schema Registry) plus a near-real-time engine (Spark micro-batches on Kubernetes) keeping segmentation current between batch cycles.

Impact: Segmentation kept current in near real time for downstream systems

SparkKubernetesKafkaDebeziumDynamoDBPython
Stack

Technical Skills

Languages

PythonSQL

Big Data & Streaming

SparkPySparkKafkaFlinkDebeziumConfluent Schema Registry

Cloud

AWS (S3, EMR, Redshift, DynamoDB, Lambda)Azure

Data Platforms

DatabricksSnowflakeDelta LakeUnity Catalog

Orchestration & IaC

AirflowDagsterTerraformDockerKubernetes

Databases

RedshiftPostgreSQLDynamoDBTrinoPrestoAthena

AI & Agentic

MCP ServersFastMCPLLM IntegrationRAGPrompt EngineeringCursor AIMLflow

BI & Visualization

TableauDatabricks AI/BIPower BIStreamlit

APIs & Frameworks

FastAPIasyncpghttpx
Why Me

The Value I Bring

AI & Agentic Systems

Built a production LLM analytics agent and the MCP server behind it: NL→SQL with confidence scoring, MLflow tracing and YAML-driven tool registration.

Performance Optimization

Cut Spark data reads 98% on a multi-terabyte daily job through partition and column pruning.

Scalability & Architecture

Build data platforms at billions of rows with millions added daily: medallion lakehouses, Delta Lake and config-driven pipeline frameworks.

Ownership & Leadership

Run platforms end-to-end that 45M+ customers depend on, from architecture through data quality to the algorithms on top.

Real-Time Capabilities

CDC streaming with Kafka and Debezium plus near-real-time update engines keeping analytical tables current in minutes, not days.

Certified Depth

13 professional certifications across AWS, Databricks, Azure and Oracle, including SA Professional and Databricks Data Engineer Professional.

Consultancy

ISTech

B2B AI & Data Engineering Consultancy

AI and data engineering consultancy serving US enterprise clients, with operations expanding into Oceania and Europe. Founded and led by a Senior Data & AI Engineer building production LLM systems hands-on for Nike and Inter&Co.

Visit ISTech →

AI & Agentic Systems

LLM agents and MCP servers built on top of the data platforms we already run.

Data Platform Architecture

Design and build production-grade data platforms: Lakehouses, Data Warehouses, and real-time streaming systems.

Cloud & Infrastructure

AWS, Azure and Databricks: migrations, optimization, and IaC with Terraform and Kubernetes.

Enterprise Consulting

Data strategy, architecture design, and fractional principal engineering for data-driven organizations.

Why Choose ISTech?

✓

Production LLM systems: agents, MCP servers, RAG on enterprise data

✓

Expert in modern data stack (Spark, Databricks, Kafka, Airflow)

✓

13+ professional certifications (AWS, Databricks, Azure)

✓

Proven track record at Nike and Inter&Co

✓

Active contracts with US enterprise clients

Credentials

Certifications & Credentials

13+ professional certifications demonstrating commitment to continuous learning and technical excellence across cloud platforms and data technologies.

Apache Airflow

Astronomer Certification DAG Authoring for Apache Airflow 3

Astronomer

Astronomer Certification for Apache Airflow 2 Fundamentals

Astronomer

AWS

AWS Certified Cloud Practitioner

Amazon Web Services Training and Certification

AWS Certified Solutions Architect - Associate

Amazon Web Services Training and Certification

AWS Certified Solutions Architect - Professional

Amazon Web Services Training and Certification

AWS Partner: Accreditation (Business)

Amazon Web Services Training and Certification

AWS Partner: Technical Accredited - Training Badge

Amazon Web Services Training and Certification

AWS Data Engineer Associate

Amazon Web Services Training and Certification

AWS Black Belt

Amazon Web Services Training and Certification

Azure

Microsoft Azure Solutions Architect Expert (AZ-305, 2023-2025)

Microsoft

Databricks

Databricks Data Engineer Professional

Databricks

Oracle

Oracle Infrastructure Foundations Associate

Oracle

Oracle Cloud Data Management Foundations

Oracle

On the Road

Global Perspective

I have worked remotely from 15+ countries across Europe, Oceania and South America, with teams in the US, Canada, Europe, India and Australia, always on client hours.

SpainPortugalFranceItalyGermanyNetherlandsBelgiumAustriaCzech RepublicPolandChileNew ZealandAustraliaIrelandUnited Kingdom
Get in Touch

Let's Connect

Interested in discussing data engineering, collaboration opportunities, or just want to chat? Feel free to reach out.