Francesco Ardita

Data Engineer & Data Analytics Expert // Cloud · ETL · BI

Data Engineer and Data Analytics Expert across STMicroelectronics, IBM and Leonardo. I design and ship ETL/ELT pipelines, cloud data platforms and BI solutions on PySpark, Google Cloud (BigQuery), Azure (Data Factory, Fabric), AWS and Databricks — owning high-level design end-to-end. I also build AI-powered analytics (RAG, prompt engineering) and dashboards (Power BI, Superset).

$ connect --linkedin github wget résumé.pdf

>>> print(open("skills.yaml").read())

languages:
  - Python
  - SQL
  - PL/SQL
  - R
  - Bash

data_engineering:
  - PySpark / Python
  - ETL / ELT
  - Data Modeling
  - Data Pipelines
  - Data Migration
  - Data Validation

bi_analytics:
  - Microsoft Power BI
  - DAX
  - Apache Superset
  - Microsoft Fabric
  - Data Visualization

cloud_infra:
  - Microsoft Azure
  - Google Cloud (BigQuery)
  - AWS
  - Docker / Kubernetes
  - Infrastructure Deploy

ai_ml:
  - RAG / LLMs
  - Prompt Engineering
  - LangChain
  - ML Models
  - Predictive Analytics

devops_management:
  - GitHub / Git
  - Azure DevOps
  - Azure Data Factory
  - Project Management
  - Agile / Scrum

# pipeline.py — bronze → silver → gold (pandas)
import pandas as pd

df = pd.read_csv("raw/events.csv")

silver = df[df["event_type"] != "test"]
silver["dt"] = pd.to_datetime(silver["ts"]).dt.date
silver["user_id"] = silver["user_id"].astype("int64")

gold = (silver
        .groupby(["dt", "region"], as_index=False)
        .agg(total_revenue=("revenue", "sum"),
             active_users=("user_id", "nunique")))

gold.to_parquet("analytics/daily_revenue.parquet")

>>> subprocess.run(["git", "log", "--graph", "--stat"], check=True)

e28d4f1 HEAD -> main Oct 2025 — Present

Data Engineer @ Leonardo

Italy · Remote/Hybrid

Lead and develop enterprise data pipelines and analytics infrastructure, owning high-level design from data modelling through to production deployment.

Lead and develop ETL/ELT pipelines in Python/PySpark on Azure Data Factory, Databricks and Microsoft Fabric, owning high-level design from data modelling to deployment.
Migrated large datasets to Google Cloud BigQuery, cutting infrastructure costs and improving query performance by ~40%.
Automated data validation and reconciliation, reducing manual QA effort and lifting data accuracy to near 100%.
Built Power BI and Apache Superset dashboards surfacing KPIs to leadership, enabling faster decision-making.
Act as technical lead for the team while developing core components end-to-end.

+PySpark+Python +Azure Data Factory+BigQuery +Power BI+Superset

9f3c2a1 Aug 2022 — Oct 2025

Data Engineer / Project Manager @ STMicroelectronics

Italy · Global (Asia projects)

Designed and built ETL pipelines in Python on Databricks, improving data accuracy and automating reporting flows.
Delivered Power BI dashboards for KPIs and multi-departmental business decisions.
Led cross-functional teams as Work Package Leader for cloud infrastructure and data provisioning projects in Asia.
Oversaw project planning, risk and change control, ensuring on-time delivery of complex data initiatives.
Partnered with senior management to align analytics strategy with business goals.

+Python+PySpark +Databricks+Power BI +DAX+Cloud +Project Mgmt

b4d81c0 Jul 2021 — Aug 2022

Data Engineer @ IBM

Italy

Optimised ETL processes, cutting reporting turnaround by ~25% and improving BI accuracy for stakeholders.
Developed and deployed data pipelines on Azure, improving data accessibility and reliability for business units.
Built Python scripts for automated data validation, reducing manual QA effort by ~30%.
Created Power BI dashboards that translated raw data into actionable insight for stakeholders.

+Python+ETL +Azure+Power BI +Data Validation

71a0e4d Jan 2021 — Jul 2021

Data Analyst @ Adora Ict S.r.l.

Italy

Acquired, processed and modelled data with Python, SQL and R, supporting internal reporting and revenue assurance.
Built PL/SQL automation scripts that cut task completion time from 3 days to 1 day (3x faster), raising operational efficiency.
Created analytical dashboards that gave the team clear visibility into revenue assurance programs.

+Python+SQL +PL/SQL+R +Analytics

0000001 root-commit Jan 2018 — Dec 2020

Credit Advisor @ Credipass

Italy

Developed and managed a client portfolio through real-estate agency partnerships, growing lending and insurance revenue by ~15% year-on-year.
Performed financial and credit-worthiness analysis for loan and mortgage eligibility, optimising liquidity and reducing credit-risk exposure.
Prepared financial reports on liquidity and credit-risk performance that informed lending decisions.

+Financial Modeling+Credit Risk +Analytics

>>> os.listdir("~/projects")

francesco@fardita:~/projects

>>> json.load(open("education.json"))

{
  "degrees": [
    {
      "degree": "Master's Degree in Corporate Finance",
      "institution": "University of Catania, Italy",
      "focus": "Financial Modeling · Econometrics · Quantitative Methods · Risk Analysis"
    },
    {
      "degree": "Bachelor's Degree in Business Administration",
      "institution": "University of Catania, Italy",
      "focus": "Economics · Accounting · Finance · Statistics"
    },
    {
      "degree": "Professional Course in Data Science & ML",
      "institution": "Tree School",
      "focus": "Python · Machine Learning · Statistical Modeling · Predictive Analytics"
    }
  ],
  "certifications": [
    { "cert": "Microsoft Certified: Fabric Analytics Engineer Associate", "issuer": "Microsoft", "year": "2026" },
    { "cert": "Power BI Data Modeling with DAX", "issuer": "LinkedIn", "year": "2025" },
    { "cert": "Databricks Lakehouse Fundamentals", "issuer": "Databricks", "year": "2023" },
    { "cert": "Python, Bash and SQL Essentials for Data Engineering", "issuer": "Coursera", "year": "2023" },
    { "cert": "Microsoft Azure Fundamentals (AZ-900)", "issuer": "Microsoft", "year": "2021" },
    { "cert": "Prompt Engineering with LangChain", "issuer": "LinkedIn", "year": "2024" }
  ]
}

>>> requests.post("https://fardita.dev/contact").json()

response — 200 OK

{
  "role": "Data Engineer · Data Analytics Expert",
  "github": "github.com/fardita",
  "linkedin": "linkedin.com/in/francesco-ardita",
  "location": "Italy · remote / hybrid"
}