Data Designer/Engineer

To be successful as a Data Designer/Engineer you should have experience with: -

• Strong experience in AWS data engineering (S3, Glue, EMR, Athena, IAM).

• Advanced Python development skills for data engineering.

• Strong hands‑on experience with Apache Spark / PySpark.

• Proven experience with Databricks (development, optimisation, notebooks, jobs).

• Hands‑on experience with Apache Airflow and Astronomer.

• Strong SQL skills and experience working with large datasets.

• Experience with CI/CD, Git‑based version control, and DevOps practices for data platforms.

• Data & Platform Knowledge.

• Solid understanding of data modelling, lakehouse architecture, and analytics‑ready data design.

• Experience implementing data quality, validation, and reconciliation frameworks.

• Familiarity with metadata, lineage, and data governance concepts. Banking / Enterprise Experience (Preferred).

• Experience working in financial services or regulated environments.

• Understanding of risk, controls, and non‑functional requirements (resilience, security, audit).

• Bachelor’s or master’s degree in computer science, Engineering, or a related field.

• Cloud or data engineering certifications (AWS / Databricks) are desirable.

Some other highly valued skills may include:

• Demonstrates ownership and accountability for technical deliverables.

• Strong problem‑solving and analytical mindset.

• Effective communicator across technical and non‑technical stakeholders.

• Mentors’ junior engineers and promotes engineering best practices.

• Champions engineering excellence, automation, and continuous improvement.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role is based in Pune.

Purpose of the role

To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. 

Accountabilities

• Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
• Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
• Development of processing and analysis algorithms fit for the intended data complexity and volumes.
• Collaboration with data scientist to build and deploy machine learning models.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the wo