Maciej Jarka, Developer in Warsaw, Poland
Maciej is available for hire
Hire Maciej

Maciej Jarka

Verified Expert  in Engineering

Data Engineer and Developer

Location
Warsaw, Poland
Toptal Member Since
June 18, 2020

Maciej is an ETL, BI, and big data engineer who's eager to share his knowledge and experience. He has over a decade of international experience under his belt, gained in projects spanning from data integration to analytics while working for industry leaders such as ING (banking) and Roche (pharma). Maciej is also quite handy with several tools including Snowflake, Netezza, Informatica, and DataStage (he’s a certified IBM DataStage trainer).

Portfolio

Fortune 100 North American Construction Equipment Manufacturer(Toptal Client)
Snowflake, SnapLogic, Data Lakes, Data Warehousing, Amazon Web Services (AWS)
SeaChange
Data Pipelines, Data Architecture, Data Warehouse Design, Data Warehousing...
ING (Belgium)
Data Pipelines, Data Architecture, Data Warehouse Design, Data Warehousing...

Experience

Availability

Part-time

Preferred Environment

SQL Server Analysis Services (SSAS), Eclipse, Git, Linux

The most amazing...

...solution I've worked on was a JDBC driver allowing you to transform your relational data into RDF graph; see more at Powerdf.com

Work Experience

Cloud Data Warehouse Architect

2019 - PRESENT
Fortune 100 North American Construction Equipment Manufacturer(Toptal Client)
  • Built foundations of enterprise data lake architecture.
  • Designed and developed data pipeline patterns to be used across the enterprise.
  • Trained business and engineering teams to use the product.
Technologies: Snowflake, SnapLogic, Data Lakes, Data Warehousing, Amazon Web Services (AWS)

Senior Data Engineer

2019 - 2021
SeaChange
  • Designed data pipelines for processing large VOD metadata datasets in Snowflake and Talend.
  • Created data warehouse structures to support advanced analytics.
  • Prepared and masked large data sets for machine-learning activities.
Technologies: Data Pipelines, Data Architecture, Data Warehouse Design, Data Warehousing, Amazon Kinesis Data Firehose, XSLT, AWS Glue, Azure Blobs, Talend ETL, Data Modeling, Git, Boto 3, Pandas, Python 3, Windows PowerShell, Amazon Athena, AWS Lambda, Amazon Kinesis, Azure Blob Storage API, Amazon S3 (AWS S3), Snowflake, SQL, Databases, ETL, Tableau, Docker, Talend

Senior Data Engineer | Team Leader | Trainer

2017 - 2019
ING (Belgium)
  • Built ETL solutions for the bank's marketing department.
  • Optimized data structures in IBM Pure Data for Analytics.
  • Trained team members in the scope of IBM DataStage.
  • Designed data structures in star schema to meet reporting requirements.
Technologies: Data Pipelines, Data Architecture, Data Warehousing, Data Warehouse Design, IBM Tivoli Workload Scheduler, Kimball Methodology, IBM InfoSphere (DataStage), Data Modeling, Git, Windows PowerShell, AWS Lambda, Amazon S3 (AWS S3), Snowflake, SQL, Databases, ETL, Netezza, Datastage

Senior BI Developer

2016 - 2017
RobertHalf (US)
  • Built management reports in SAP Business Objects.
  • Designed SAP BO universes.
  • Optimized Oracle data warehouse for reporting.
Technologies: Data Pipelines, Data Architecture, Data Warehousing, Data Warehouse Design, SAP BusinessObjects (BO), Kimball Methodology, Data Modeling, Oracle RDBMS, SQL, Databases, ETL, Oracle, SAP BusinessObjects Data Service (BODS)

Senior ETL Developer

2015 - 2017
Roche Pharmaceuticals
  • Developed ETL solutions for large market data sets.
  • Optimized Teradata database structures for reporting.
  • Gathered requirements from the data science team.
  • Built a database to graph solutions with Talend and SPARQL.
Technologies: Data Pipelines, Data Architecture, Data Warehousing, Data Warehouse Design, XSLT, Talend ETL, Kimball Methodology, Data Modeling, Git, PL/SQL, SQL, Databases, ETL, RDF, SPARQL, Teradata, Talend, Informatica PowerCenter

Senior ETL Developer

2014 - 2015
Ascen
  • Developed ETL processes with IBM DataStage and Microsoft Integration Services.
  • Generated reports in SAP BusinessObjects for LOT Polish Airlines.
  • Created analytical cubes with Microsoft Analysis Services for LOT Polish Airlines.
Technologies: Data Pipelines, Data Architecture, Data Warehouse Design, Data Warehousing, Netezza, Kimball Methodology, IBM InfoSphere (DataStage), Data Modeling, Git, PL/SQL, SQL, Databases, ETL, SQL Server Analysis Services (SSAS), Datastage

Data Integration Developer

2013 - 2014
Roche Pharmaceuticals
  • Integrated enterprise data sources such as Oracle, Salesforce, and LDAP.
  • Built ETL and data virtualization solutions.
Technologies: Data Pipelines, Data Architecture, Data Warehousing, Data Warehouse Design, Data Modeling, PL/SQL, SQL, Databases, ETL, Java, Oracle RDBMS, JBoss

Master Data Management (MDM) Developer

2011 - 2013
ValueTank
  • Designed a data model for a master data management solution.
  • Developed Java software components embedded in IBM MDM platform.
  • Collected a client's requirements related to change requests.
Technologies: Data Pipelines, Data Architecture, XSLT, IBM Tivoli Workload Scheduler, Netezza, Kimball Methodology, IBM InfoSphere (DataStage), Data Modeling, Windows PowerShell, PL/SQL, Master Data Management (MDM), Oracle RDBMS, Web Services, SQL, Databases, Management, Java

Software Developer

2008 - 2011
Comarch
  • Developed an advanced data mining and integration platform called ADMIRE (Admire-project.eu).
  • Built data-mining models for churn prediction and cross-selling.
  • Constructed Java-based components for the platform.
Technologies: Data Pipelines, XSLT, Git, Windows PowerShell, PostgreSQL, PL/SQL, Oracle RDBMS, Web Services, SQL, Databases, Data Mining, Weka, Java

PoweRDF

PoweRDF is a JDBC driver allowing the user to transform their relational data into an RDF graph. It is portable to all ETL tools supporting JDBC. Please refer to the website for more details.

Trend Catcher for Twitter

Trend Catcher is an academic app for a research team led by Szymin Piatek from the University of Warwick. It aggregates Twitter data per location enabling trend analyses.

The DATA Bonanza (Book)

I am a guest co-author of a data mining-related book released by Wiley in 2013. This work was done while I was also a member of the ADMIRE project (Admire-project.eu). You can find my chapter about churn prediction in the section on analytical CRMs.
2010 - 2012

Master of Science (MSc) Degree in Computer Science

Warsaw University of Technology - Warsaw, Poland

2006 - 2010

Engineer's Degree in Computer Science

Warsaw University of Technology - Warsaw, Poland

DECEMBER 2021 - PRESENT

SnowPro Advanced Architect

Snowflake (Udemy)

JANUARY 2021 - PRESENT

SnowPro Core

Snowflake

JANUARY 2017 - PRESENT

C2090-424-EN InfoSphere DataStage v11.3

IBM

JANUARY 2014 - PRESENT

00-N50 IBM PureData System for Analytics (Netezza) Technical Mastery

IBM

JANUARY 2012 - PRESENT

000-M78 — IBM Initiate Master Data Service Technical Mastery

IBM

JANUARY 2011 - PRESENT

P2090-086 IBM InfoSphere Master Data Management — PIM Technical Mastery

IBM

JANUARY 2010 - PRESENT

1Z0-851 — Oracle Certified Programmer for the Java 2 Platform, SE 6.0

Oracle

Libraries/APIs

Azure Blob Storage API, Pandas

Tools

IBM InfoSphere (DataStage), Talend ETL, Informatica PowerCenter, IBM Tivoli Workload Scheduler, Amazon Athena, AWS Glue, Git, Weka, Tableau, Boto 3, SnapLogic, Amazon Kinesis Data Firehose

Languages

Snowflake, SQL, Java, SPARQL, RDF, XSLT, Python 3

Storage

Databases, Data Pipelines, Netezza, Master Data Management (MDM), PL/SQL, Azure Blobs, Amazon S3 (AWS S3), PostgreSQL, Oracle RDBMS, Datastage, SQL Server Analysis Services (SSAS), Data Lakes, Teradata

Paradigms

ETL, Kimball Methodology, Management

Frameworks

Windows PowerShell

Platforms

Linux, AWS Lambda, Eclipse, JBoss, Talend, Oracle, Amazon Web Services (AWS), Docker

Other

Data Warehousing, Data Architecture, Data Warehouse Design, Data Modeling, SAP BusinessObjects (BO), Web Services, Amazon Kinesis, SAP BusinessObjects Data Service (BODS), Data Mining

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

1

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring