Madrid, Spain · Available June 2026

Divyansh
Shrivastava

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Python · SQL · PySpark LLMs · RAG · NL-to-SQL AWS · GCP · Databricks dbt · Airflow · Kafka Real Madrid Internship
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01 / About

Three domains.
Two disciplines.
One engineer.

I'm a Senior Data & AI Engineer with 5 years of experience across high-volume production data systems, enterprise data platforms, and — most recently — AI SaaS delivery at Real Madrid.

During my Real Madrid internship, I worked as an AI engineer: understood the business problem, ran social media and commercial analytics, then built and shipped ClubOS — an end-to-end AI SaaS tool used directly by senior club stakeholders.

My background spans three distinct domains and two engineering disciplines — which is unusual and deliberately so. I don't prototype AI demos. I ship systems that real stakeholders use.

Currently completing an MSc in Sports Analytics at Universidad Europea de Madrid (Real Madrid Graduate School). Finishing June 2026. Actively looking for my next role.

Honeywell Technology Solutions
Built high-volume production data pipelines processing streams from 1,000+ connected sources — owning ingestion, storage optimization, and query performance at product-company standards.
HashedIn by Deloitte
Architected enterprise cloud data platforms serving cross-functional teams across marketing, BI, operations, and risk. Tech lead mentoring 4 engineers.
Real Madrid C.F.
Operated as an AI engineer — owning the full stack from data ingestion to LLM-powered application delivery for non-technical decision-makers.
5+ Years Experience
3 Major Domains
15K+ Players in ScoutIQ
40% Pipeline Speedup
02 / Experience

Where I've
shipped.

Oct 2025 — Jun 2026
Madrid, Spain
AI Engineer (Internship)
Real Madrid C.F.
  • Identified core business problem: disconnected social media signals, commercial performance data, and match data with no unified decision-support layer for non-technical leadership
  • Built ClubOS end-to-end — integrated YouTube, Reddit, historical commercial data, and match performance into a single AI SaaS platform with LLM-generated scenario narratives
  • Designed and implemented full data layer: ingestion pipelines, domain data products, Gold-layer transformation on Databricks, and retrieval architecture for LLM context
  • Delivered to senior club stakeholders operating to professional football department standards — a working tool in active use, not a prototype
PythonDatabricksDelta LakeLLMsRAGAnthropic APIReactFastAPIdbt
Jun 2021 — Oct 2024
Bengaluru, India
Senior Data Engineer
HashedIn by Deloitte
  • Architected cloud data lakehouse on AWS using Apache Iceberg — multi-zone design (raw → curated → semantic) serving 6+ cross-functional teams with column-level security
  • Designed semantic data layer on AWS and GCP — star schemas, wide tables, aggregation layers for QuickSight and Power BI; dbt-governed transformation with full lineage tracking
  • Implemented CDC ingestion using Kafka and AWS Glue Streaming — replaced daily batch loads with sub-hour SLA delivery across critical reporting domains
  • Deployed RAG pipeline using Amazon Bedrock — first LLM system shipped to production in the team
  • Led developer experience improvements: shared Python libraries, GitLab CI pipelines — cut onboarding time 50%; mentored 4 engineers, reduced production defects 30%
PythonPySparkdbtAirflowKafkaAWSGCPDatabricksDelta LakeIcebergTerraform
Oct 2019 — May 2021
Bengaluru, India
Big Data Engineer
Honeywell Technology Solutions
  • Built high-volume production data pipelines processing streams from 1,000+ connected sources — owned ingestion with schema validation and deduplication at source
  • Optimised distributed query performance by 35% through strategic partitioning, bucketing, and cluster tuning
  • Designed data flows supporting predictive maintenance AI models — engineered feature-rich datasets enabling early-failure detection
HadoopHiveSqoopHDFSOracle DBMySQLPythonSQL
03 / Projects

Things I've
built.

Real Madrid Internship 01

ClubOS

AI Commercial Intelligence Platform

End-to-end AI SaaS tool built during Real Madrid internship. Automatically processes digital channel data, benchmarks against elite European clubs, and delivers an AI-generated ranked priority board to club leadership.

52Metrics
5Clubs
103Mo. History
23Auto Tests
PythonDatabricksLLMsRAGReactFastAPIdbtDelta Lake
GitHub →
MSc Final Project 02

ScoutIQ

Football Scouting Intelligence Platform

Production-grade football scouting platform covering 15,000+ players across Europe's top 5 leagues. Role-based scoring engine, player similarity engine, and an AI Scout Assistant answering natural language recruitment queries via the Anthropic API.

15K+Players
13Profiles
5Leagues
20+Metrics
FastAPIPostgreSQLDuckDBAnthropic APINL-to-SQLReactAirflowDocker
GitHub →
03

Urban Pulse

Multi-Cloud Data Lakehouse

Production portfolio project ingesting NYC 311, NYPD crime, TfL London transit, AirNow EPA, and Open-Meteo data into a multi-cloud lakehouse. Full dbt transformation layer with 33+ automated data quality tests.

5APIs
33+Unit Tests
4Airflow DAGs
3Clouds
GCPAWSDatabricksdbtAirflowDockerBigQueryTerraform
GitHub →
04

StatsBomb Viz

Tactical Analysis Dashboard

Interactive football analytics dashboard using StatsBomb open event data. Pass networks, shot maps, player heatmaps, pressing metrics. Identified Leicester City's 2015/16 title was built on deliberately low pressing intensity — 3rd lowest PPDA among top-6 clubs.

PythonmplsoccerStreamlitStatsBomb APIPlotlypandas
GitHub →
04 / Skills

My toolkit.

AI & LLM Engineering
LLMs · RAG PipelinesProduction
NL-to-SQL · Prompt EngineeringProduction
Anthropic API · Amazon BedrockProduction
MLflow · Feature EngineeringAdvanced
Data Engineering
Python · SQLExpert
PySpark · DatabricksExpert
dbt · Apache AirflowExpert
Kafka · CDC IngestionAdvanced
Cloud Platforms
AWS (S3, Glue, EMR, Bedrock)Expert
GCP (BigQuery, Dataflow)Advanced
Azure (Synapse, Data Factory)Advanced
Terraform · DockerAdvanced
Football Analytics
StatsBomb · Wyscout · SkillCornerAdvanced
xG · xA · PPDA · Progressive MetricsAdvanced
mplsoccer · Plotly · StreamlitAdvanced
Also familiar with
FastAPIReactPostgreSQLDuckDBScalaDelta LakeApache IcebergTableauPower BISnowflake
05 / Education

Academic
foundation.

2025 — 2026
MSc Sports Analytics
Universidad Europea de Madrid
Real Madrid Graduate School
  • Football performance analytics, event & tracking data pipelines
  • ML for scouting & player valuation, statistical modelling
  • Data internship with Real Madrid — ClubOS AI platform
  • Final Project: ScoutIQ — 15K+ player scouting intelligence platform
2019
PG Diploma, Big Data & Analytics
IACSD, Pune
  • Distributed computing & Hadoop ecosystem
  • Data warehousing and analytics engineering
  • Technical foundation for enterprise data engineering career
2014 — 2018
B.E. Mechanical Engineering
ITM Universe, Gwalior
  • Engineering fundamentals, systems thinking
  • Analytical problem-solving grounding

Let's build
something
together.

I'm finishing my MSc in June 2026 and actively looking for my next role. If you're building an AI product, a data platform, or a sports analytics system — let's talk.

Email divyyansh99@gmail.com → LinkedIn linkedin.com/in/divyyansh05 → GitHub github.com/divyyansh05 →
Open to opportunities
What I'm looking for
  • AI Engineer at VC-backed startups
  • Senior Data Engineer at product companies
  • GTM-adjacent AI roles
  • Football Analytics · Scouting Analyst at clubs
  • Sports data companies (Opta, StatsBomb, Hudl)