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Lead Data Architect
Luxoft
Chicago, USA
Full-time
Lead
Discovered 1 weeks ago
• Readiness to work until 8.00 pm CET (no need to do overtimes) • Overall years of experience required 8+ (at least 1+ year in an Architect position) • Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years). • Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval. • Strong 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. • Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses. • Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing. • Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) • Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages. • Experience integrating metadata and governance processes into cloud-based data platforms • Certification in Azure, Databricks, or other relevant technologies is an added advantage • Experience with cloud-based analytical databases. • Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix. • Experience with Python and Python-based ETL tools. • Experience with shell scripting in Bash, Unix or windows shell is preferable. • Demonstrated 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.
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Ready to ScanKey skills for this role
• Readiness to work until 8.00 pm CET (no need to do overtimes) • Overall years of experience required 8+ (at least 1+ year in an Architect position) • Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years). • Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval. • Strong 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. • Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses. • Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing. • Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) • Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages. • Experience integrating metadata and governance processes into cloud-based data platforms • Certification in Azure, Databricks, or other relevant technologies is an added advantage • Experience with cloud-based analytical databases. • Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix. • Experience with Python and Python-based ETL tools. • Experience with shell scripting in Bash, Unix or windows shell is preferable. • Demonstrated 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.
Key Skills for This Role
• Readiness to work until 8.00 pm CET (no need to do overtimes) • Overall years of experience required 8+ (at least 1+ year in an Architect position) • Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years). • Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval. • Strong 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. • Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses. • Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing. • Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) • Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages. • Experience integrating metadata and governance processes into cloud-based data platforms • Certification in Azure, Databricks, or other relevant technologies is an added advantage • Experience with cloud-based analytical databases. • Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix. • Experience with Python and Python-based ETL tools. • Experience with shell scripting in Bash, Unix or windows shell is preferable. • Demonstrated 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.
Full Job Posting
Skills
- Readiness to work until 8.00 pm CET (no need to do overtimes) • Overall years of experience required 8+ (at least 1+ year in an Architect position) • Strong, recent hands-on expertise with Azure Data Factory and Synapse is a must (3+ years). • Strong expertise in designing and implementing data models, including conceptual, logical, and physical data models, to support efficient data storage and retrieval. • Strong 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. • Extensive experience with building robust and scalable ETL/ELT pipelines to extract, transform, and load data from various sources into data lakes or data warehouses. • Ability to integrate data from disparate sources, including databases, APIs, and external data providers, using appropriate techniques such as API integration or message queuing. • Proficiency in designing and implementing data warehousing solutions (dimensional modeling, star schemas, Data Mesh, Data/Delta Lakehouse, Data Vault) • Proficiency in SQL to perform complex queries, data transformations, and performance tuning on cloud-based data storages. • Experience integrating metadata and governance processes into cloud-based data platforms • Certification in Azure, Databricks, or other relevant technologies is an added advantage • Experience with cloud-based analytical databases. • Experience with Azure MI, Azure Database for Postgres, Azure Cosmos DB, Azure Analysis Services, and Informix. • Experience with Python and Python-based ETL tools. • Experience with shell scripting in Bash, Unix or windows shell is preferable. • Demonstrated 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.
Responsibilities
- We are looking for Data Architect 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.
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