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, operating across various sectors of the banking industry. They are known for their commitment to innovation and excellence in delivering robust financial solutions. The company fosters a culture of continuous improvement and professional development, empowering its employees to thrive in a dynamic environment.
About the role.
This role involves building and maintaining sophisticated data systems, including pipelines, data warehouses, and data lakes. You will be instrumental in ensuring data accuracy, accessibility, and security across the organization. The position requires a strong focus on developing and implementing data architectures that support efficient data transfer and processing, contributing to the evolution of the digital landscape.
What you will do.
- Build and maintain data architectures and pipelines to ensure durable, complete, and consistent data transfer and processing.
- Design and implement data warehouses and data lakes, managing appropriate data volumes and velocity while adhering to security measures.
- Develop processing and analysis algorithms suitable for complex data volumes and types.
- Collaborate with data scientists to build and deploy machine learning models.
- Perform prescribed activities in a timely manner and to a high standard, consistently driving continuous improvement.
- Take responsibility for end results of a team’s operational processing and activities.
- Advise and influence decision-making within your area of expertise.
- Take ownership for managing risk and strengthening controls in relation to your work.
What you bring.
- 4–8 years of experience in data engineering.
- Advanced SQL query writing and performance tuning skills.
- Proficiency with Teradata for enterprise data warehousing.
- Strong experience with PySpark for distributed data processing.
- Familiarity with Hadoop big data tools and architecture.
- Strong Linux Shell Scripting skills for automation and data handling.
- Understanding of cloud-based data platforms and services, particularly AWS.
- Prior exposure to AWS, including experience with data migration or analytics, is a strong plus.
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