Lead Data Engineer

pstrongProject description /strong /ppThe primary goal of the project is the modernization, maintenance and development of an eCommerce platform for a big US-based retail company, serving millions of omnichannel customers each week./ppbr/ppSolutions are delivered by several Product Teams focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart./ppbr/ppCurrent overriding priorities are new brands onboarding, re-architecture, database migrations, migration of microservices to a unified cloud-native solution without any disruption to business./ppbr/ppstrongResponsibilities /strong /ppbr/ppWe are looking for Data Engineer who will be responsible for designing a solution for a big retail company.The main focus is to support processing of big data volumes and integrate solution to current architecture./ppbr/ppstrongSkills /strong /ppbr/ppReadiness to work until 8.00 pm CET (no need to do overtimes) /ppOverall years of experience required 8+ (at least 1+ year in a Lead/Architect position) /ppStrong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years)./ppStrong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval./ppStrong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks, pySpark for building scalable and reliable data solutions./ppExtensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses./ppAbility to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing./ppProficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) /ppProficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages./ppExperience integrating metadata and governance processes into cloud-based data platforms /ppCertification in Azure, Databricks, or other relevant technologies is an added advantage /ppExperience with cloud-based analytical databases./ppExperience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix./ppExperience with Python and Python-based ETL tools./ppExperience with shell scripting in Bash, Unix or windows shell is preferable./ppDemonstrated ability to lead cross-functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and effectively communicate with stakeholders at all organizational levels./ppbr/ppNice to have /ppExperience with Elasticsearch /ppFamiliarity with containerization and orchestration technologies (Docker, Kubernetes)./ppTroubleshooting and Performance Tuning: Ability to identify and resolve performance bottlenecks in data processing workflows and optimize data pipelines for efficient data ingestion and analysis./ppCollaboration and Communication: Strong interpersonal skills to collaborate effectively with stakeholders, data engineers, data scientists, and other cross-functional teams./ppAbility to plan, estimate and track progress of implementing features /ppComputer Science and data science academic and education credentials /ppbr/ppstrongOther /strong /ppstrongLanguages /strong /ppEnglish: B2 Upper Intermediate /p

ppbr/ppstrongSkills /strong /ppbr/ppReadiness to work until 8.00 pm CET (no need to do overtimes) /ppOverall years of experience required 8+ (at least 1+ year in a Lead/Architect position) /ppStrong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years). /ppStrong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval. /ppStrong knowledge of Microsoft Azure, including Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, and Azure Databricks, pySpark for building scalable and reliable data solutions. /ppExtensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses. /ppAbility to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing. /ppProficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) /ppProficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages. /ppExperience integrating metadata and governance processes into cloud-based data platforms /ppCertification in Azure, Databricks, or other relevant technologies is an added advantage /ppExperience with cloud-based analytical databases. /ppExperience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix. /ppExperience with Python and Python-based ETL tools. /ppExperience with shell scripting in Bash, Unix or windows shell is preferable. /ppDemonstrated ability to lead cross-functional engineering teams, define technical strategy and architecture, drive delivery of complex data platforms, mentor engineers, and effectively communicate with stakeholders at all organizational levels. /ppbr/ppNice to have /ppExperience with Elasticsearch /ppFamiliarity with containerization and orchestration technologies (Docker, Kubernetes). /ppTroubleshooting and Performance Tuning: Ability to identify and resolve performance bottlenecks in data processing workflows and optimize data pipelines for efficient data ingestion and analysis. /ppCollaboration and Communication: Strong interpersonal skills to collaborate effectively with stakeholders, data engineers, data scientists, and other cross-functional teams. /ppAbility to plan, estimate and track progress of implementing features /ppComputer Science and data science academic and education credentials /ppbr/ppstrongOther /strong /ppstrongLanguages /strong /ppEnglish: B2 Upper Intermediate /p