Lead Azure Data Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global player in the computer software industry, known for delivering innovative digital solutions and data-driven insights. They operate at a significant scale, fostering a culture of technical excellence and continuous professional growth. The organization is committed to leveraging cutting-edge cloud technologies to solve complex enterprise challenges.
About the role.
We are seeking a seasoned Lead Azure Data Engineer to spearhead the design and development of robust, scalable data solutions within a cloud-native environment. In this pivotal role, you will leverage your extensive expertise in Azure and Snowflake to build high-performance ETL/ELT pipelines, ensuring seamless data integration and governance across enterprise systems. You will act as a technical leader, translating complex business requirements into high-impact data architectures.
What you will do.
- Architect and implement end-to-end ETL/ELT pipelines utilizing Azure Data Factory, Snowflake, and DBT.
- Develop and maintain complex data integration workflows, ensuring high availability and data integrity.
- Author highly optimized SQL queries to facilitate advanced data extraction and transformation processes.
- Partner with cross-functional stakeholders to translate intricate business requirements into scalable technical architectures.
- Proactively monitor, troubleshoot, and tune data pipelines to maximize performance and reliability.
- Champion data governance, quality standards, and comprehensive technical documentation.
- Collaborate effectively with data architects, analysts, and DevOps teams to drive cloud-native excellence.
What you bring.
- 9–11 years of professional experience in data engineering, with a deep focus on the Azure ecosystem and Snowflake.
- Proven mastery of Azure Data Factory (ADF) for complex orchestration and automation.
- Advanced proficiency in SQL and SnowSQL for large-scale data warehousing.
- Hands-on experience implementing transformation logic using DBT.
- Demonstrated ability to manage large-scale datasets within cloud-based environments.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
- Exceptional problem-solving, communication, and collaborative skills.
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