Data Engineering Lead.
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 leading global professional services firm specializing in accounting, finance, and advisory solutions. With a vast international presence, they are committed to driving innovation through advanced data analytics and cutting-edge technology. They foster a collaborative culture that values technical excellence and professional growth.
About the role.
The Data Engineering Lead will oversee the analytics data platform, focusing on the maintenance, optimization, and reliability of complex data pipelines. This role is critical in ensuring high-quality data delivery by troubleshooting production issues, conducting root cause analysis, and implementing scalable solutions. You will work in a hybrid environment in Bengaluru, collaborating with cross-functional teams to support customer-critical data initiatives.
What you will do.
- Act as the primary technical lead for diagnosing, troubleshooting, and resolving complex customer-facing data and pipeline issues.
- Conduct thorough root cause analysis and implement long-term fixes to prevent recurrence of system incidents.
- Collaborate with cross-functional teams to ensure data integrations meet high standards of accuracy, consistency, and usability.
- Establish and lead structured incident management processes, including on-call practices and post-incident reviews.
- Design, build, and continuously improve scalable ETL/ELT pipelines to ensure high availability and data integrity.
- Implement data quality frameworks and validation processes to maintain reliable production environments.
What you bring.
- Strong expertise in Python and Java for building production-grade data solutions.
- Proven experience with Apache Spark and Kafka for managing large-scale real-time and batch data pipelines.
- Deep understanding of production support, incident management, and root cause analysis in distributed systems.
- Strong proficiency in SQL and performance tuning for customer-critical workloads.
- Hands-on experience with microservices architecture, focusing on reliability and fault tolerance.
- Expertise in big data technologies including Hive, HBase, and Parquet.
- Experience with data quality frameworks, validation, and reconciliation processes.
- Familiarity with Gen-AI and AI solutions is highly preferred.
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