Teradata Developer Resume

• Responsible for creating a high-scalable environment to analyze telecommunication network data logs, ensuring the platform’s ability to monitor network quality effectively.
• Implementing technologies such as Hortonworks Data Platform (HDP), Apache Spark, Elasticsearch, and Kibana to build the analytical platform.
• Collaborating closely with stakeholders and teams to integrate various components, including Spark, Elasticsearch, and ECE (Elastic Cloud Enterprise), to ensure seamless functionality.

• Implementing and quality-assuring data ingestion and data mart creation processes for over 50 data sources as defined by the customer, ensuring accuracy and efficiency.
• Overseeing a team of engineers, providing guidance and supervision in DevOps tasks and data integration activities to ensure project success.
• Leveraging technologies such as HDP, HDF, Kylo, Nifi, Apache Spark, Semantic Layer, Kerberos, Ansible, and Jupyter to implement the required data processes and achieve project goals.

• Designing an analytical platform for analyzing data from IoT sensors installed on trucks, focusing on standard use cases like risk analysis and predictive maintenance.
• Ensuring compliance with GDPR regulations by implementing a secure access layer within the platform architecture.
• Integrating various technologies such as Hadoop, HDP, Kylo, Apache Hive, Apache Nifi, Microsoft Azure, Teradata, and IBM WMQ to develop and deploy the analytical platform.

• Analyzing the existing data system architecture across the organization, conducting workshops with key stakeholders, and preparing a target platform design and capability assessment.
• Designing a multilayered data repository to store and manage data effectively, ensuring scalability and performance.
• Delivering a detailed roadmap for the designed system, outlining steps for implementation and future enhancements.

• Designing a new analytical platform and processes to optimize the usage of historical studies data, including analysis of existing platform and implementing new tools and processes.
• Designing a new data lake to store and manage data effectively, including ELT processes for text analytics and structured data processing.
• Implementing technologies such as Cloudera, Hadoop, Elasticsearch, Kibana, Kylo, Nifi, Tikka, Maven, Apache Spark, Scala, Python, and Apache Hive to achieve project objectives.

• Conducting workshops with customers to document the existing architecture of the analytical ecosystem and create a capabilities assessment to define recommendations and roadmap.
• Creating a concept for a centralized Data Hub (Data Lake combined with Data Warehouse), outlining architecture and capabilities required to meet business needs.
• Implementing recommendations from the capabilities assessment phase, including kerberization of the HDP cluster and ELT processes running on the cluster.

• Implementing ingestion processes for the Data Lake, ensuring efficient and reliable data acquisition from various sources.
• Utilizing technologies such as CDH, Vagrant, Kylo, Apache Hive, Apache Spark, and Apache Nifi to develop and deploy the ingestion processes.
• Collaborating with stakeholders and teams to ensure alignment with project goals and requirements, and communicating progress and issues effectively.

• Designing an analytical ecosystem based on Teradata UDA solutions to combine Data Warehouse, Data Discovery Platform, and Data Lake implemented on Hadoop technology.
• Providing essential security measures to the analytical ecosystem, ensuring data privacy and compliance with regulations.
• Integrating technologies such as HDP, Teradata, Oracle, and Data Virtualization to achieve the desired analytical capabilities and functionalities.

• Conducting workshops with customers to document the existing architecture of the analytical ecosystem and create a capabilities assessment to define recommendations and roadmap.
• Planning and implementing recommendations from the capabilities assessment phase, including kerberization of the HDP cluster and ELT processes running on the cluster.
• Utilizing technologies such as HDP, Teradata, Oracle, and Data Virtualization to develop and deploy the recommended solutions.

• Working as a member of an international architecture task force to create Data Lake Design patterns using Teradata UDA stack, focusing on Storage and Data Processing layers.
• Delivering design patterns for Storage and Data Processing layers of the Data Lake, ensuring alignment with best practices and client requirements.
• Collaborating with team members and stakeholders to ensure the successful delivery and adoption of the design patterns across different projects and organizations.

• Leading the creation of one of the first big Hadoop Clusters in Poland, including designing the overall platform architecture and data flow processes.
• Implementing technologies such as CDH, Apache Hive, Apache Hadoop, Spring, Python, MapReduce, Apache Flume, MySQL, PostgreSQL, and Pentaho to develop and deploy the Hadoop Cluster.
• Designing a Lambda Architecture based analytics solution, enabling real-time data processing and analytics on the Hadoop Cluster.