Lead Data Engineer

To be successful as a Lead Data Engineer you should have experience with:

• Strong knowledge of ETL and dependent technologies in the below scope:
• Python
• Extensive hands-on PySpark
• Data Warehousing concept
• Strong SQL knowledge
• AWS working exposure
• Big Data Hadoop
• Experience in Relational Databases like Oracle, SQL Server, and PL/SQL
• Understanding of Agile methodologies as well as SDLC life cycles and processes.
• Expertise in UNIX scripts, DB & TWS.
• Strong Understanding of Data warehousing and Data lakes
• Requirement Gathering & Analysis and other SDLC phases

You may be assessed on 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 out of 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

• 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 work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc). to solve problems creatively and effectively.
• Communicate complex information. Complex information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.