Moses O.

Data Engineer

Moses is a skilled Data Engineer with eight years of experience designing and optimizing data solutions across various industries. He has deep expertise in SQL, Python, Spark, Databricks, DBT, Airflow, Kafka, and cloud platforms such as Azure, GCP, and AWS.

One of his key achievements includes refactoring data pipelines for a client by migrating their legacy system to Databricks. This transformation was particularly impactful as he successfully tailored the solution to meet the distinct needs of Data Engineering, Machine Learning, and Analytics Engineering teams, resulting in a robust and adaptable data infrastructure.

With a strong ability to align stakeholder requirements with technical implementations, Moses consistently delivers innovative, scalable, and efficient data solutions that drive business success.

Main expertise
  • Microsoft Power BI
    Microsoft Power BI 6 years
  • SSAS
    SSAS 6 years
  • SSIS
    SSIS 8 years
Other skills
  • Kubernetes
    Kubernetes 5 years
  • Terraform
    Terraform 4 years
  • Keras
    Keras 3 years
Moses
Moses O.

Estonia

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Selected experience

Employment

  • Data Engineer

    Bondora - 1 year 11 months

    • Managed and developed scalable data pipelines using Azure DevOps for continuous integration and continuous deployment (CI/CD);

    • Facilitated data ingestion from diverse external sources and operational databases into the bronze, silver, and gold layers of a Lakehouse architecture;

    • Leveraged a custom-built framework utilizing Python, SQL, Azure Databricks, SSIS, Azure Event Hubs, and Azure Data Factory to streamline data processing workflows;

    • Designed and implemented dashboarding solutions using Looker to provide actionable insights;

    • Orchestrated workflows with DBT (Data Build Tool) and Databricks Workflows to ensure seamless data transformations and efficient pipeline operations.

    Technologies:

    • Technologies:
    • Microsoft Power BI Microsoft Power BI
    • SSIS SSIS
    • Kubernetes Kubernetes
    • Postman Postman
    • JSON JSON
    • REST API REST API
    • Databricks Databricks
    • Grafana Grafana
    • Tableau Tableau
    • ETL ETL
    • Flask Flask
    • Selenium Selenium
    • FastAPI FastAPI
    • Pydantic Pydantic
    • NumPy NumPy
    • Pandas Pandas
    • PyTorch
    • DevOps DevOps
    • Docker Docker
    • SQL SQL
    • Azure Azure
    • Python Python
    • Azure Blob storage Azure Blob storage
    • Apache Kafka Apache Kafka
    • Apache Airflow Apache Airflow
    • Azure Cloud Azure Cloud
    • MSSQL MSSQL
    • PowerShell PowerShell
    • SharePoint SharePoint
    • Bash Bash
    • Git Git
    • Terraform Terraform
    • Azure Data Factory Azure Data Factory
    • Data Modeling
    • ELT
    • PostgreSQL PostgreSQL
    • MS 365 Power Apps MS 365 Power Apps
    • Azure Event Hubs Azure Event Hubs
    • Confluent Confluent
  • Data Engineer

    Breakwater Technology - 1 year 7 months

    • Managed, built, and secured both batch and real-time streaming data pipelines to process and analyze large datasets efficiently;

    • Identified trends in complex datasets to deliver valuable insights and support data-driven decision-making;

    • Developed and maintained data warehouses to transform raw data into structured and accessible formats for clients;

    • Designed and implemented reusable frameworks for storing and processing external data sources;

    • Utilized technologies such as SQL, Python, Scala, Apache Spark, DBT, BigQuery, and Airflow for scalable data processing and transformation;

    • Integrated Kafka Connect for real-time data streaming and seamless connectivity with external systems;

    • Created interactive and insightful data visualizations using Google Data Studio to communicate results effectively.

    Technologies:

    • Technologies:
    • Scala Scala
    • Kubernetes Kubernetes
    • Postman Postman
    • JSON JSON
    • REST API REST API
    • ETL ETL
    • Flask Flask
    • FastAPI FastAPI
    • Pydantic Pydantic
    • NumPy NumPy
    • Pandas Pandas
    • PyTorch
    • DevOps DevOps
    • Docker Docker
    • SQL SQL
    • Python Python
    • Azure Blob storage Azure Blob storage
    • Apache Kafka Apache Kafka
    • Apache Airflow Apache Airflow
    • Google Cloud Google Cloud
    • AWS AWS
    • Bash Bash
    • BigQuery BigQuery
    • Git Git
    • Looker Looker
    • Terraform Terraform
    • Data Modeling
    • ELT
    • Apache Spark Apache Spark
    • Salesforce Salesforce
    • Confluent Confluent
  • Data Engineer

    Dubai Holding - 2 months

    • Designed and developed big data solutions to manage golden customer records across various business verticals, ensuring data accuracy and consistency;

    • Consolidated large datasets from diverse sources by leveraging technologies such as SQL, Python, Azure Databricks, Azure Event Hubs, and Azure Data Factory;

    • Applied the principles of the medallion data architecture to create structured and efficient data layers (bronze, silver, gold) for optimized data management and analytics;

    • Utilized Azure Data Lake and Azure Synapse Analytics to enable scalable data storage and processing;

    • Implemented CI/CD pipelines with Azure DevOps to streamline development and deployment processes for data solutions.

    Technologies:

    • Technologies:
    • Microsoft Power BI Microsoft Power BI
    • Kubernetes Kubernetes
    • Postman Postman
    • JSON JSON
    • REST API REST API
    • Databricks Databricks
    • ETL ETL
    • Flask Flask
    • FastAPI FastAPI
    • Pydantic Pydantic
    • NumPy NumPy
    • Pandas Pandas
    • PyTorch
    • DevOps DevOps
    • Docker Docker
    • SQL SQL
    • Azure Azure
    • Python Python
    • Azure Blob storage Azure Blob storage
    • Apache Kafka Apache Kafka
    • Azure Cloud Azure Cloud
    • MSSQL MSSQL
    • PowerShell PowerShell
    • SharePoint SharePoint
    • Bash Bash
    • Git Git
    • Azure Data Factory Azure Data Factory
    • Data Modeling
    • ELT
    • Azure Event Hubs Azure Event Hubs
  • Data Engineer

    PricewaterhouseCoopers (PwC) - 2 years 2 months

    • Managed, built, and secured Microsoft SQL Server (2017, 2019, Azure SQL) databases and data pipelines, enabling enterprise data integration across heterogeneous systems for PwC offices in 12 countries using Databricks and Azure Data Factory;

    • Migrated legacy data pipelines to Azure Databricks, improving performance and scalability;

    • Built ETL processes using Azure Data Factory to support key business workflows and ensure seamless data operations;

    • Co-led an integration team, delivering interfaces for a significant digital transformation project in the Finance sector;

    • Designed Power BI dashboards for senior management, providing real-time, at-a-glance insights through key performance indicators (KPIs);

    • Enhanced SSRS query response time by 15% through query restructuring after thorough execution plan analysis;

    • Drove data platform improvements, including capacity planning to increase scalability and support business growth;

    • Ensured data security, quality, and governance across all data platforms to maintain compliance and operational integrity.

    Technologies:

    • Technologies:
    • Microsoft Power BI Microsoft Power BI
    • SSAS SSAS
    • SSIS SSIS
    • Kubernetes Kubernetes
    • T-SQL T-SQL
    • Postman Postman
    • JSON JSON
    • REST API REST API
    • Databricks Databricks
    • Tableau Tableau
    • ETL ETL
    • Keras Keras
    • Flask Flask
    • Selenium Selenium
    • FastAPI FastAPI
    • Pydantic Pydantic
    • NumPy NumPy
    • Pandas Pandas
    • PyTorch
    • DevOps DevOps
    • Docker Docker
    • SQL SQL
    • Azure Azure
    • Python Python
    • Azure Blob storage Azure Blob storage
    • Apache Kafka Apache Kafka
    • Apache Airflow Apache Airflow
    • Google Cloud Google Cloud
    • Azure Cloud Azure Cloud
    • MSSQL MSSQL
    • PowerShell PowerShell
    • SharePoint SharePoint
    • MuleSoft Anypoint Platform
    • UIPath UIPath
    • Bash Bash
    • BigQuery BigQuery
    • Git Git
    • Looker Looker
    • Terraform Terraform
    • Azure Data Factory Azure Data Factory
    • Data Modeling
    • ELT
    • MS 365 Administration MS 365 Administration
    • VMware vSphere VMware vSphere
    • Workday HCM Workday HCM
  • Data Architect – February 2016 to May 2019

    PricewaterhouseCoopers (PwC) - 3 years 3 months

    • Managed data platforms and pipelines for critical business systems across NoSQL, MySQL, and MSSQL databases, ensuring optimal performance and reliability;

    • Designed data architecture, implemented data warehousing solutions, and coordinated infrastructure changes to meet business requirements;

    • Contributed to a 30% reduction in database administration task time by developing PowerShell scripts to automate installation, configuration, monitoring, patch management, and upgrades;

    • Conducted research on emerging data platform technologies and practices, producing thought leadership documentation to enhance the technical expertise of the team;

    • Developed and tested Disaster Recovery (DR) strategies for operational MSSQL databases and OLAP cubes, implementing clustering and replication solutions to achieve a Recovery Time Objective (RTO) of 4 minutes and 99.9% system availability.

    Technologies:

    • Technologies:
    • Microsoft Power BI Microsoft Power BI
    • SSAS SSAS
    • SSIS SSIS
    • Kubernetes Kubernetes
    • T-SQL T-SQL
    • Postman Postman
    • JSON JSON
    • REST API REST API
    • Databricks Databricks
    • ETL ETL
    • Keras Keras
    • Flask Flask
    • Selenium Selenium
    • FastAPI FastAPI
    • Pydantic Pydantic
    • NumPy NumPy
    • Pandas Pandas
    • PyTorch
    • DevOps DevOps
    • Docker Docker
    • Azure Azure
    • Python Python
    • Azure Blob storage Azure Blob storage
    • Apache Kafka Apache Kafka
    • Apache Airflow Apache Airflow
    • Google Cloud Google Cloud
    • Azure Cloud Azure Cloud
    • MSSQL MSSQL
    • PowerShell PowerShell
    • SharePoint SharePoint
    • UIPath UIPath
    • Bash Bash
    • BigQuery BigQuery
    • Git Git
    • Terraform Terraform
    • Azure Data Factory Azure Data Factory
    • Data Modeling
    • ELT
    • MS 365 Administration MS 365 Administration
    • VMware vSphere VMware vSphere
  • Solutions Developer

    PricewaterhouseCoopers (PwC) - 2 years 2 months

    • Developed, maintained, and supported application programs with backends in MySQL, Microsoft SQL Server (2012, 2014), and Oracle 11g, ensuring reliable performance and functionality;

    • Led and architected multitier application design, testing, and deployment, ensuring scalability and robust functionality;

    • Conducted complex technical reviews of database systems to optimize performance, resource utilization, and data integrity;

    • Mentored development teams in Agile best practices, resulting in decreased development time and improved team efficiency;

    • Participated as a member of a special forensic audit team for Local Authorities in Ghana, analyzing transactional data in Microsoft SQL Server and Oracle databases using T-SQL scripts to identify fraudulent activities.

    Technologies:

    • Technologies:
    • VB.NET VB.NET
    • SSAS SSAS
    • SSIS SSIS
    • T-SQL T-SQL
    • JSON JSON
    • REST API REST API
    • Databricks Databricks
    • ETL ETL
    • FastAPI FastAPI
    • Java Java
    • SQL SQL
    • Azure Azure
    • Python Python
    • Azure Blob storage Azure Blob storage
    • Azure Cloud Azure Cloud
    • MSSQL MSSQL
    • PowerShell PowerShell
    • SharePoint SharePoint
    • UIPath UIPath
    • C# C#
    • Git Git
    • Data Modeling
    • ELT
    • MS 365 Administration MS 365 Administration
    • VMware vSphere VMware vSphere
  • Technical Support Engineer

    Newmont Corporation - 11 months

    • Assisted in planning, designing, testing, troubleshooting, and deploying applications, as well as physical and virtual server environments and workstations, ensuring seamless operation;

    • Initiated and facilitated ITIL processes, including Incident Management, Request Fulfillment, Access Management, Problem Management, and Knowledge Management, to enhance IT service delivery and support;

    • Played a key role in the companywide migration from a legacy enterprise resource planning (ERP) system to SAP, providing comprehensive end-user training and support;

    • Prepared detailed requirements and specifications for new systems and modifications to existing systems, including supporting documentation and design, to align with organizational needs.

    Technologies:

    • Technologies:
    • SAP SAP
    • MSSQL MSSQL
    • PowerShell PowerShell

Education

  • MSc.Management

    Estonian Business School · 2022 - 2023

  • MSc.Data Science

    Middlesex University · 2019 - 2021

  • MSc.Management Information Systems

    Coventry University · 2014 - 2015

  • BSc.Computer Science

    Valley View University · 2008 - 2012

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