Senior Data Engineer

Role Overview: You will leverage strong collaboration skills and independently develop and design highly complex data sets and ETL processes on the Azure ecosystem. Your work will involve various Azure Data Engineering related problems such as the development of a data warehouse, Advanced Stored Procedures, ETL pipelines, Reporting, Data Governance, and AI implementation. You should have hands-on experience in SQL, Python, Pyspark, ETL development, Azure Data Factory, and AI implementation knowledge. Key Responsibilities: - Implement GenAI technologies. - Manage cross-functional technical teams and coordinate delivery across analytics, development, and AI tracks. - Utilize cloud environments and design API-based solutions. - Translate business problems into structured data engineering and analytics solutions. - Prioritize workloads, manage dependencies, and track progress for timely, high-quality deliverables. - Implement scalable processes for data validation, governance, and version control. - Understand Business Requirements and convert them into process flows and codes, with a special preference for SQL-based stored procedures. - Manage the full data engineering and analytics delivery lifecycle. - Ensure alignment between business needs, data capabilities, and technical execution. - Promote collaboration, agile delivery, and continuous improvement within the team. - Encourage the adoption of modern data technologies and AI frameworks. - Identify opportunities to automate manual processes and improve data workflows. - Keep abreast of emerging analytics tools, MLOps practices, and AI trends to enhance team capabilities. Qualifications Required: - Bachelors degree in computer science, Data Science, Engineering, or a related discipline. - Preferred certifications in Azure Data engineering and GenAI technologies. - 6+ years of experience in analytics, data engineering, or application development, with at least 2 years in a leadership or project management capacity. - Exposure to AI/ML development lifecycles and integration into analytics/engineering platforms. - Experience working in agile environments with sprint planning, retrospectives, and release management. - Understanding of data architecture, CI/CD for analytics, and version control systems (Git). Note: Zen Data Shastra is a hybrid consulting firm that focuses on helping organizations build capabilities around data science and analytics. ZDS offers full stack Data capabilities including Data Engineering, Data Science, and Decision Science with expertise in building solutions based on Artificial Intelligence and Machine Learning across industries. The team at Zen Data Shastra has contributed to the success of over 10 Fortune 500 clients globally in realizing the value of data and influencing decisions. Website: Address: Zen Data Shastra, 1st Floor, Gopalan Millennium Towers, ITPL main road, Brookfield Bengaluru Role Overview: You will leverage strong collaboration skills and independently develop and design highly complex data sets and ETL processes on the Azure ecosystem. Your work will involve various Azure Data Engineering related problems such as the development of a data warehouse, Advanced Stored Procedures, ETL pipelines, Reporting, Data Governance, and AI implementation. You should have hands-on experience in SQL, Python, Pyspark, ETL development, Azure Data Factory, and AI implementation knowledge. Key Responsibilities: - Implement GenAI technologies. - Manage cross-functional technical teams and coordinate delivery across analytics, development, and AI tracks. - Utilize cloud environments and design API-based solutions. - Translate business problems into structured data engineering and analytics solutions. - Prioritize workloads, manage dependencies, and track progress for timely, high-quality deliverables. - Implement scalable processes for data validation, governance, and version control. - Understand Business Requirements and convert them into process flows and codes, with a special preference for SQL-based stored procedures. - Manage the full data engineering and analytics delivery lifecycle. - Ensure alignment between business needs, data capabilities, and technical execution. - Promote collaboration, agile delivery, and continuous improvement within the team. - Encourage the adoption of modern data technologies and AI frameworks. - Identify opportunities to automate manual processes and improve data workflows. - Keep abreast of emerging analytics tools, MLOps practices, and AI trends to enhance team capabilities. Qualifications Required: - Bachelors degree in computer science, Data Science, Engineering, or a related discipline. - Preferred certifications in Azure Data engineering and GenAI technologies. - 6+ years of experience in analytics, data engineering, or application development, with at least 2 years in a leadership or project management capacity. - Exposure to AI/ML development lifecycles and integration into analytics