Mateusz Cieślak, Developer in Warsaw, Poland
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Mateusz Cieślak

Verified Expert  in Engineering

Bio

Mateusz is an experienced data engineer with more than 20 projects delivered in areas of data analytics and IT implementations. He is an expert in big data technologies (Hadoop, Python, Apache Spark, Azure) and SQL (T-SQL) and is known for building high-performing ETL/ELT data pipelines. At PwC, Mateusz developed a large volume data mart to profile over 300 million citizens by more than 500 variables and an analytics engine to recommend optimal promotional actions with more than 20,000 products.

Portfolio

ProData Consult
Python, PySpark, Apache Airflow, Apache Hive, Microsoft SQL Server...
PwC Poland
PySpark, Python, SQL, Azure, Tableau, Microsoft SQL Server, JavaScript, C#.NET...
PwC Poland
SQL, Hadoop, Spark, Microsoft SQL Server

Experience

  • SQL - 10 years
  • Python - 10 years
  • Spark - 6 years
  • Tableau - 6 years
  • Microsoft SQL Server - 6 years
  • Hadoop - 6 years
  • Azure - 3 years
  • Azure Data Factory - 3 years

Availability

Part-time

Preferred Environment

Windows, Linux, Visual Studio Code (VS Code), PyCharm

The most amazing...

...project I've delivered was the IFRS9 benchmark testing tool. I served as a developer and an analyst to deliver the app in less than a month.

Work Experience

Senior Data Engineer

2021 - 2022
ProData Consult
  • Developed E2E ETL flows for a client from the banking industry that responsible for the transformation of billions of records. Data was used to train fraud detection models.
  • Optimized existing data pipelines, which, in some cases reduced execution time by 95%.
  • Set up best practices within the team around MLOps, code quality (all newly developed pipelines having 100% unit test coverage) and data quality.
Technologies: Python, PySpark, Apache Airflow, Apache Hive, Microsoft SQL Server, Apache Cassandra, Agile Software Development, Quality Assurance (QA), Data Engineering, Data Pipelines, ETL, Data Architecture, Spark, Data Governance, Business Intelligence (BI), Hadoop, Pandas

Senior Data Engineer

2018 - 2021
PwC Poland
  • Developed and maintained a large volume data mart used to profile US citizens. Each citizen (300 million+) was profiled by more than 500 direct features.
  • Implemented an IFRS 9 benchmark testing tool to forecast credit stability in terms of repayment for hundreds of thousands of credit exposures.
  • Implemented ISO 20000 standard within the Data Analytics team, consisting of more than 100 people.
Technologies: PySpark, Python, SQL, Azure, Tableau, Microsoft SQL Server, JavaScript, C#.NET, Apache Hive, Apache Impala, Agile Software Development, ITIL, Quality Assurance (QA), Databricks, Data Engineering, Data Pipelines, Data Visualization, PostgreSQL, MySQL, SQL Server Integration Services (SSIS), ETL, Data Architecture, Spark, Data Governance, Business Intelligence (BI), Hadoop, Java, Pandas

Data Engineer

2016 - 2018
PwC Poland
  • Developed an analytics engine used to recommend optimal promotional actions for a leading retail store chain in Poland. The engine included more than 20,000 products and gave recommendations based on real client receipt data.
  • Created a demand and profitability forecasting tool for a leading food manufacturer in Poland. The utility covered 300 products and gave predictions based on past invoices and terms of contract extracted using text mining algorithms.
  • Developed an application handling the sale process of financial assets in accordance with MiFID II. Acted as a full-stack developer and application architect.
Technologies: SQL, Hadoop, Spark, Microsoft SQL Server

Customer Data Mart

Developed and maintained a large volume data mart used to profile US citizens. Each of over 300 million citizens was profiled by more than 500 variables. The data mart included behavioral features (coming from various profiling external vendors) such as geo-matched features from the official Census Bureau datasets and remediated address data.

I also oversaw the technical implementation of the data mart's CCPA (California Consumer Privacy Act) procedure.

Fraud Analytics

Acted as a data engineer within the team in charge of developing models detecting various types of financial fraud. I automated existing data flows and transformations and optimization, which in some cases resulted in a 95% performance increase in terms of execution time. Introduced best practices within the fraud analytics team regarding code quality (high unit test coverage) and data quality.

MiFID II Application

Developed a web application handling the sale process of financial assets in accordance with MiFID II. Acted as a full stack developer for the front and back ends and database developer/data architect. Did business requirements collection and presentation to prospective clients.

IFRS9 Benchmark Testing Tool

Implemented an IFRS 9 benchmark testing tool to forecast credit stability in terms of repayment for hundreds of thousands of credit exposures. The analysis was made based on credit exposure parameters and Reuters's interest rates forward contracts data. Acted as a database architect and developer, BI developer; the results were presented in Tableau dashboards.
2014 - 2017

Master's Degree in Finance and Accounting

Warsaw School of Economics - Warsaw

2011 - 2014

Bachelor's Degree in Finance and Accounting

Warsaw School of Economics - Warsaw

JUNE 2021 - PRESENT

ISTQB Certified Tester Foundation Level

ISTQB® - International Software Testing Qualifications Board

JUNE 2018 - PRESENT

ITIL Foundation

AXELOS Global Best Practice

Libraries/APIs

PySpark, Pandas

Tools

Tableau, Apache Airflow, Apache Impala, PyCharm

Languages

Python, SQL, JavaScript, Java, C#.NET

Frameworks

Spark, Hadoop

Paradigms

ETL, Agile Software Development, Business Intelligence (BI), ITIL

Storage

Microsoft SQL Server, Apache Hive, Data Pipelines, SQL Server Integration Services (SSIS), PostgreSQL, MySQL

Platforms

Azure, Windows, Linux, Databricks, Visual Studio Code (VS Code)

Other

Data Engineering, Data Architecture, Data Visualization, Azure Data Factory, Apache Cassandra, Quality Assurance (QA), Data Governance, Corporate Finance

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