Jurijs Jefimovs, Developer in Riga, Latvia
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Jurijs Jefimovs

Verified Expert  in Engineering

Bio

Jurijs is an experienced Business Intelligence (BI) engineer with 17 years of experience building data warehouses (DWH) and BI applications. He specializes in developing self-service BI environments tailored to your organization's needs, from building DWH and dimensional models (star schemas) to delivering BI applications and user training. With a robust background in eCommerce, supply chain, iGaming, and beyond, Jurijs ensures impactful analytics solutions for diverse industries.

Portfolio

Luminor
Performance Tuning, Performance Analysis, Cloud Architecture...
LeoVegas Group
Performance Analysis, Google Cloud Platform (GCP), APIs...
Betsson Group
SQL Performance, Performance Tuning, Performance Analysis, APIs...

Experience

  • Data Visualization - 13 years
  • ETL Development - 13 years
  • Dimensional Modeling - 12 years
  • Data Warehouse Design - 12 years
  • Microsoft Power BI - 5 years
  • Tableau - 5 years
  • QlikView - 3 years
  • Snowflake - 2 years

Availability

Part-time

Preferred Environment

ELK (Elastic Stack), Google BigQuery, Google Data Studio, Qlik Sense, QlikView, Tableau, Microsoft Power BI, SQL Server Integration Services (SSIS), Azure, Snowflake

The most amazing...

...thing I've rolled out was self-service BI with environment set up, data warehousing, ETL development, dimensional modeling, app development, and user training.

Work Experience

Data Engineer | Data Architect | Data Platform Development Lead

2018 - PRESENT
Luminor
  • Created dashboards and reports with Tableau for the eCommerce supply chain area to help better understand inventory positioning, planning, order fulfillment rate, product stale, and order path from check out to delivery.
  • Engineered a data analytical layer using Snowflake, dbt, Tableau, Power BI, and Git as a foundation data layer for eCommerce needs. Developed data pipelines, dimensional modeling (star schema), and automated BI dashboards and reports.
  • Implemented a real-time data streaming platform to enable DSS systems, covering use cases like real-time transaction search, fraud monitoring, and interactive product recommendations.
  • Designed and prototyped various systems, successfully advocating them in front of the enterprise architecture committees.
  • Introduced pub/sub message delivery semantics for data integration between various back-end components and DSS systems.
  • Conducted rigorous tests for delivered solutions, including functional, non-functional, performance, and penetration tests.
  • Migrated customer transaction history from the old core system into a new data platform.
Technologies: Performance Tuning, Performance Analysis, Cloud Architecture, Amazon Web Services (AWS), APIs, Business Intelligence (BI), Streaming, Requirements Analysis, Business Analysis, Impact Analysis, Big Data Architecture, Big Data, Data Visualization, Remote Team Leadership, Remote Work, Team Leadership, Leadership, ETL Implementation & Design, Elasticsearch, NoSQL, Database Architecture, Data Architecture, Data Pipelines, Data Lakes, Data Engineering, Data Modeling, Database Modeling, SQL, Kafka Streams, Amazon EKS, Apache NiFi, Amazon S3 (AWS S3), Amazon MSK, Architecture, Data Analysis, API Integration, Data Build Tool (dbt), Decision Support, Decision Support Systems, DSS, SharePoint, Microsoft Power BI

BI Engineer

2017 - 2020
LeoVegas Group
  • Developed reports analyzing user visits, interests, and behavior on web pages using clickstream data and Google Analytics.
  • Developed Google Analytics reports encompassing landing page analyses, acquisition overviews, path exploration (customer journey), engagement summaries, and conversion rates.
  • Utilized Google Analytics, Tableau, and BigQuery to create reports for digital marketing, including landing pages, acquisition overviews, customer journey, engagement overview, and conversion rates.
  • Created BI applications with QlikView, Tableau, and Power BI for marketing, customer acquisition, CRM, responsible gaming, payments, and finance.
  • Implemented ETL processes and data marts with QlikView Publisher to consolidate data for decision support systems (DSS).
  • Established a data warehouse on Google Cloud Platform using dimensional modeling to enable DSS (BI tools) systems to utilize consolidated and verified data sources.
  • Developed a BI/DSS application for configuring payment providers' pricing models and commission calculations using Google Sheets (configuration tool), Google Big Query (ETL), and Data Studio (reporting).
  • Created and supported various automated reports with Qlik NPrinting.
Technologies: Performance Analysis, Google Cloud Platform (GCP), APIs, Business Intelligence Training, Business Intelligence (BI), Requirements Analysis, Business Analysis, Impact Analysis, Analytical Thinking, Analytics, Analytical Dashboards, Visualization Tools, Visualization, Dashboard Design, Dashboards, Dashboard Development, Big Data, Data Visualization, Team Leadership, Remote Work, Database Architecture, Data Architecture, Data Pipelines, Data Lakes, Database Modeling, Data Modeling, SQL, ETL Implementation & Design, ETL, Google Data Studio, Google BigQuery, Tableau, Qlik NPrinting, QlikView, Architecture, Data Analysis, API Integration, Artificial Intelligence (AI), Decision Support, Decision Support Systems, DSS, Google Analytics, SharePoint, ClickStream, Microsoft Power BI

BI Data Engineer

2016 - 2017
Betsson Group
  • Developed reports for digital marketing using Google Analytics, Data Studio, and Big Query, covering areas like landing pages, acquisition, customer journey, engagement, and conversion rates.
  • Created BI applications, including customer lifetime value (CLV) and customer classification with Qlik Sense.
  • Analyzed user visits and behavior on web pages using clickstream and Google Analytics data.
  • Established a self-service BI environment with Qlik Sense, from setting up the environment, data modeling, and development of applications to user training.
  • Conducted prototyping of real-time analytics with ELK stack and a data analytical layer on top of the big data platform for enhanced query speed, evaluating technologies like Jethro Data.
Technologies: SQL Performance, Performance Tuning, Performance Analysis, APIs, Business Intelligence Training, Business Intelligence (BI), Analytical Dashboards, Analysis, Analytics, Visualization Tools, Visualization, Dashboard Development, Dashboards, Dashboard Design, Big Data, Data Visualization, ETL Implementation & Design, Elasticsearch, NoSQL, Data Architecture, Data Pipelines, Data Lakes, Data Engineering, Data Modeling, SQL, Tableau, Microsoft SQL Server, ELK (Elastic Stack), Jethro, Apache Hive, QlikView, Qlik Sense, Architecture, Data Analysis, API Integration, Artificial Intelligence (AI), Decision Support, Decision Support Systems, DSS, Google Analytics, MySQL, SharePoint, ClickStream, Microsoft Power BI

Lead Software Developer

2015 - 2016
Intrum Justitia
  • Developed an analytical layer on top of Big Data (Cloudera's CDH) using Apache Hive for ETL, Apache Impala for query processing, and Tableau for BI applications, enhancing DSS/BI systems support.
  • Designed and developed a consolidated dimensional model to unify data from various sources, providing a single data model for diverse business reporting needs and enabling the use of consolidated data across the organization by DSS systems.
  • Introduced self-service BI adoption among business users, advocating for its benefits in internal conferences across different offices throughout the EU, particularly with Tableau.
Technologies: Performance Tuning, SQL Performance, Performance Analysis, APIs, Business Intelligence Training, Business Intelligence (BI), Analytical Thinking, Analysis, Analytics, Visualization Tools, Dashboards, Analytical Dashboards, Visualization, Dashboard Development, Dashboard Design, Big Data, Data Visualization, ETL Implementation & Design, NoSQL, Database Architecture, Big Data Architecture, Data Architecture, Data Pipelines, Data Lakes, Data Engineering, Data Modeling, Database Modeling, SQL, Apache Kylin, Apache Hive, Apache Impala, Tableau, Architecture, Data Analysis, Microsoft SQL Server, API Integration, Artificial Intelligence (AI), Decision Support, Decision Support Systems, DSS, MySQL

Systems Analyst

2009 - 2015
Idea Port Riga
  • Developed and maintained the data warehouse, ETL, and BI application processes for the insurance, telco, and pharmacy retailer companies.
  • Customized CRM system to fix reporting data gaps and improve ETL processes (CDC).
  • Built a data archiving tool to offload historical data from CRM to improve CRM's performance, which helped to decrease customer service response time.
  • Developed POC of fraud detection BI application, which helped find fraudulent cases and analyze the reasons behind insurance claims.
  • Created the POC of a product recommendation engine for pharmacy retailers, which could increase sales by offering similar products based on transactional data.
Technologies: SQL Performance, Performance Tuning, APIs, Business Intelligence Training, Business Intelligence (BI), Visualization Tools, Visualization, Dashboard Design, Dashboard Development, Dashboards, Data Visualization, ETL Implementation & Design, Database Architecture, Data Architecture, Data Pipelines, Data Modeling, Database Modeling, SQL, Siebel CRM, Oracle Data Miner, SQL Server Reporting Services (SSRS), SQL Server Analysis Services (SSAS), SQL Server Integration Services (SSIS), Microsoft SQL Server, Oracle Warehouse Builder (OWB), Informatica PowerCenter, IBM Cognos Business Intelligence, Oracle RDBMS, Oracle BI EE 11g, Architecture, Data Analysis, API Integration, Artificial Intelligence (AI), Decision Support, Decision Support Systems, DSS, MySQL, SharePoint

Analyst Programmer

2007 - 2009
Rietumu Bank
  • Built the customer investment portfolio performance report for customers.
  • Created customer account statements and other regulatory reports automation.
  • Developed the automated generation of customers' account statements and send-outs by email.
Technologies: SQL Performance, Performance Tuning, Performance Analysis, APIs, Business Intelligence (BI), Data Visualization, ETL Implementation & Design, Database Architecture, Data Architecture, Data Pipelines, Data Modeling, Database Modeling, SQL, Bloomberg API, Excel VBA, Microsoft Excel, Microsoft Access, T-SQL (Transact-SQL), Microsoft SQL Server, Crystal Reports, Data Analysis, Decision Support, Decision Support Systems, DSS

Senior Developer

2006 - 2007
Accenture
  • Developed the integration layer between legacy systems and Oracle Siebel CRM (Java).
  • Customized various Siebel CRM applications for clients.
  • Improved performance of Siebel CRM system for a few clients by reviewing and refactoring custom scripts.
Technologies: Performance Tuning, Performance Analysis, APIs, Data Modeling, Database Architecture, SQL, Java, Siebel CRM, Data Analysis

Experience

Data Streaming Platform

I led and supervised the implementation of the data streaming platform for daily banking needs (end users/retail). We have successfully released the first version of data streaming platform services and created a good foundation for future services that can recommend and communicate the right information at the right time to customers. This can potentially increase user engagement and the usage of banking products and services.

Self-service BI Environment

I introduced a self-service BI environment inside a company that helped reduce reports and data analysis delivery time. First, I set up the Qlik Sense environment and built data marts used by business users for ad hoc report creation and sharing. Then, I trained business analysts on creating data marts for their domain areas inside Qlik Sense to help them react faster to business analytical needs.

Analytical Layer on Top of Big Data

Designed and implemented an analytical layer on top of the Hadoop raw data, which allowed building of a flexible BI application layer to satisfy the company's reporting and ad hoc query needs. Instead of building custom reporting solutions with map-reduce, I've proposed making a dimensional model (star schema) on top of the Hadoop with Hive's help as the ETL engine and Impala for accelerating queries over Hive metadata. I also introduced self-service BI with Tableau. This was completely my initiative, which I completed in 2015 when people had zero trust in such technologies.

Tableau Public Profile

https://public.tableau.com/profile/jurijs.jefimovs#!/
Tableau public profile where you can see examples of Tableau applications/dashboards. There you can find examples of interactive dashboards, geospatial charts, Sankey diagrams, applications build using public data sources such as GDELT, Riga Open Data (new-birth statistics), Kaggle competition, and more.

DWH and Analytical Layer With Snowflake

I spearheaded the development of a DWH and analytical layer, incorporating star schema, dimensional modeling, and data marts to meet the company's internal analytical needs. Additionally, I implemented many dashboards with Tableau and Microsoft Power BI.

Tech stack: Snowflake, dbt, GitHub, SQL, Tableau, Microsoft Power BI

Product Recommendation Engine for Pharmacy Retail

I built a product recommendation engine with SQL Server Analysis Services for pharmacy retailer based on transaction history data.
Tech stack: SQL Server Analysis Services, MS SQL Server, MS Power BI

Fraud Detection Engine for Insurance Company

I developed a fraud detection engine (outlier detection engine) to identify fraudulent/suspicious insurance claims based on insurance claims history.

Tech stack: Oracle Database, Oracle Data Miner, SQL, PL/SQL, Oracle Business Intelligence (BI) EE

Customer Lifetime Value

I created a customer lifetime value (CLV/CLVT) model to predict the value of the customers being in different time frames with the company. This helped to assess the costs associated with customer acquisition and to personalize product offerings based on predicted value.

Customer Segmentation for iGaming Company

I built a customer segmentation model and integrated it into the analytical data layer, enabling data analysis of business needs. This helped enrich the product recommendation engine.

Tech stack: Python, Microsoft SQL Server, Tableau, Power BI

Education

2014 - 2015

Data Science Specialization in Data Science

Johns Hopkins University - Coursera

2006 - 2009

Master's Degree in Computer Science

Transport and Telecommunication Institute - Riga, Latvia

2002 - 2006

Bachelor's Degree in Computer Science

Transport and Telecommunication Institute - Riga, Latvia

Certifications

MARCH 2024 - PRESENT

Python and Pandas for Data Engineering

Duke University | via Coursera

MARCH 2019 - PRESENT

MongoDB Performance

MongoDB University

OCTOBER 2017 - PRESENT

Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform

Google Cloud

OCTOBER 2017 - PRESENT

Serverless Data Analysis with Google BigQuery and Cloud Dataflow

Google Cloud

SEPTEMBER 2017 - PRESENT

Google Cloud Big Data and Machine Learning

Google Cloud

SEPTEMBER 2017 - PRESENT

Google Cloud Platform Big Data and Machine Learning

Coursera

AUGUST 2016 - PRESENT

Big Data Modeling and Management Systems

University of California San Diego | via Coursera

MAY 2016 - PRESENT

Hadoop Platform and Application Framework

University of California San Diego | via Coursera

JANUARY 2016 - PRESENT

Tableau Advanced Trainings

Udemy

AUGUST 2015 - PRESENT

Big Data XSeries

edX

MAY 2015 - PRESENT

Data Science Specialization

Coursera

APRIL 2015 - PRESENT

Pattern Discovery in Data Mining

University of Illinois at Urbana-Champaign | via Coursera

Skills

Libraries/APIs

Bloomberg API, Spark ML, TensorFlow, Pandas

Tools

Tableau, Apache Impala, Informatica PowerCenter, Oracle Warehouse Builder (OWB), Microsoft Power BI, Google Analytics, Qlik Sense, ELK (Elastic Stack), Talend ETL, Apache NiFi, Amazon EKS, Kafka Streams, Siebel CRM, Crystal Reports, Microsoft Access, Microsoft Excel, GitHub, Git, Tableau Desktop Pro, Power BI Desktop, Apache Beam, Google Cloud Dataproc

Languages

SQL, Snowflake, T-SQL (Transact-SQL), Excel VBA, Java, R, Python, JavaScript

Paradigms

Database Design, Dimensional Modeling, ETL, ETL Implementation & Design, Requirements Analysis, Business Intelligence (BI), MapReduce

Platforms

SharePoint, QlikView, Qlik NPrinting, Oracle BI EE 11g, Apache Kafka, Amazon Web Services (AWS), Google Cloud Platform (GCP), Oracle Database, Azure, Jupyter Notebook, Visual Studio Code (VS Code)

Storage

Database Architecture, Database Modeling, MySQL, PL/SQL, Apache Hive, Microsoft SQL Server, SQL Server Integration Services (SSIS), Data Lakes, Data Pipelines, NoSQL, Elasticsearch, SQL Performance, PostgreSQL, MongoDB, Amazon S3 (AWS S3), Oracle RDBMS, SQL Server Analysis Services (SSAS), SQL Server Reporting Services (SSRS), Oracle PL/SQL, SQL Server 2016, Databases

Frameworks

Hadoop, Apache Spark

Industry Expertise

Project Management

Other

Data Warehouse Design, ETL Development, Data Modeling, Data Engineering, Data Architecture, Data Visualization, Dashboard Development, Dashboards, Dashboard Design, Visualization, Visualization Tools, Analytical Dashboards, Analytics, Analytical Thinking, Analysis, Impact Analysis, Business Analysis, Business Intelligence Training, Data Analysis, API Integration, Decision Support, Decision Support Systems, DSS, Google Data Studio, Google BigQuery, Performance Analysis, Architecture, Artificial Intelligence (AI), Amazon MSK, Jethro, Apache Kylin, IBM Cognos Business Intelligence, Oracle Data Miner, Data Science, Performance Tuning, Big Data Architecture, Leadership, Team Leadership, Remote Work, Remote Team Leadership, NiFi, IT Project Management, Big Data, Streaming, APIs, Cloud Architecture, Open Data, Data Transformation, Data Build Tool (dbt), Tableau Server, DAX, Machine Learning, Oracle BI, Programming, Statistics, Natural Language Processing (NLP), A/B Testing, Regression Modeling, Classification Algorithms, Data Preprocessing, Data Cleaning, Data Products, ClickStream, Data Mining, Sequential Pattern Mining, Publish–Subscribe Pattern, Cloud Computing, Data Management, Data Structures

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