Senior Data Architect

Job Description Role Overview: As a Senior Data Platform Engineer at our company, you will have a significant impact on building and enhancing the Databricks capabilities within the team. Your role will involve designing and implementing scalable data solutions using Databricks and Azure Synapse to support analytics and business intelligence initiatives. Additionally, you will play a key role in contributing to architectural decisions, mentoring a growing team of data professionals, and ensuring data quality, security, and governance across all data platforms and pipelines. Key Responsibilities: - Design and implement scalable data solutions using Databricks and Azure Synapse. - Contribute to architectural decisions and best practices for data engineering, data warehousing, and data integration. - Build and lead a high-performing data team, including hiring, mentoring, and establishing development standards. - Collaborate with cross-functional teams to resolve issues and implement improvements. - Develop and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources. - Communicate effectively with stakeholders to provide project updates, issue resolution, and system performance. - Maintain detailed documentation of data platform architecture, ETL processes, operational procedures, and issue resolutions. - Stay current with industry trends and emerging technologies to enhance data platform capabilities. Qualifications Required: - 6+ years of experience in data engineering or analytics roles. - Strong hands-on experience with Databricks (Spark, Delta Lake, MLflow) and Azure Synapse Analytics. - Proven experience in building and scaling data teams and mentoring junior engineers. - Solid understanding of data architecture, data modeling, and cloud-native data solutions. - Proficiency in SQL, Python, and Spark. - Experience with CI/CD pipelines, version control (e.g., Git), and DevOps practices in a data environment. - Excellent communication and stakeholder management skills. - Strong analytical and problem-solving abilities. - Ability to work independently as well as in a collaborative team environment. - Bachelor's degree in computer science, Information Technology, or a related field. - Relevant Microsoft or Databricks certification is a plus. About the Company: Allianz Technology is the global IT service provider for Allianz, driving the digitalization of the Group with over 13,000 employees in 22 countries. They deliver end-to-end IT solutions for Allianz in the digital age, covering IT infrastructure projects, application platforms, and more. Allianz Technology is committed to diversity and equal opportunities in the workplace, welcoming applications from all individuals regardless of background. Join us at Allianz Technology and let's care for tomorrow. Role Overview: As a Senior Data Platform Engineer at our company, you will have a significant impact on building and enhancing the Databricks capabilities within the team. Your role will involve designing and implementing scalable data solutions using Databricks and Azure Synapse to support analytics and business intelligence initiatives. Additionally, you will play a key role in contributing to architectural decisions, mentoring a growing team of data professionals, and ensuring data quality, security, and governance across all data platforms and pipelines. Key Responsibilities: - Design and implement scalable data solutions using Databricks and Azure Synapse. - Contribute to architectural decisions and best practices for data engineering, data warehousing, and data integration. - Build and lead a high-performing data team, including hiring, mentoring, and establishing development standards. - Collaborate with cross-functional teams to resolve issues and implement improvements. - Develop and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources. - Communicate effectively with stakeholders to provide project updates, issue resolution, and system performance. - Maintain detailed documentation of data platform architecture, ETL processes, operational procedures, and issue resolutions. - Stay current with industry trends and emerging technologies to enhance data platform capabilities. Qualifications Required: - 6+ years of experience in data engineering or analytics roles. - Strong hands-on experience with Databricks (Spark, Delta Lake, MLflow) and Azure Synapse Analytics. - Proven experience in building and scaling data teams and mentoring junior engineers. - Solid understanding of data architecture, data modeling, and cloud-native data solutions. - Proficiency in SQL, Python, and Spark. - Experience with CI/CD pipelines, version control (e.g., Git), and DevOps practices in a data environment. - Excellent communication and stakeholder management skills. - Strong analytical and problem-solving abilities. - Ability to work independently as well as in a collaborative team environment. -