Senior 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 leading global financial services institution with a significant presence in the banking sector. They are committed to leveraging cutting-edge technology to drive innovation and maintain excellence in their data-driven operations. The organization fosters a collaborative culture that values strategic thinking, risk management, and professional development.
About the role.
This role involves designing, developing, and maintaining scalable data pipelines and modern data platform architectures. You will lead complex data engineering initiatives, ensuring that data is accurate, accessible, and secure while collaborating with cross-functional teams to deliver high-performance data products. The position requires a blend of technical expertise and leadership to influence decision-making and drive operational effectiveness.
What you will do.
- Build and maintain robust data architectures and pipelines to ensure consistent and reliable data processing.
- Design and implement scalable data warehouses and data lakes that adhere to strict security and governance standards.
- Develop advanced processing and analysis algorithms to handle complex data volumes and velocity.
- Lead and mentor a team of engineers, setting objectives and fostering an environment of excellence.
- Collaborate with data scientists to build, deploy, and optimize machine learning models.
- Advise stakeholders on data strategy and contribute to the development of organizational policies.
- Identify and mitigate risks while strengthening controls across data engineering workflows.
- Engage in complex analysis of internal and external data sources to solve business problems creatively.
What you bring.
- 8–15 years of professional experience in data engineering and ETL development.
- Expertise in Python and PySpark for building scalable data pipelines.
- Strong hands-on experience with AWS cloud services including S3, Glue, EMR, Lambda, and DynamoDB.
- Proficiency in modern data platform architectures such as Data Lakes and Lakehouse models.
- Experience with Databricks or Snowflake for large-scale data processing.
- Solid understanding of Git-based source control and automated testing approaches.
- Proven ability to lead collaborative assignments and guide team members through complex projects.
- Excellent communication skills with the ability to translate complex technical information for diverse stakeholders.
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