Key Responsibilities:

Delivery Management

- Own end-to-end delivery of data engineering, analytics, and platform modernization initiatives.
- Manage project scope, timelines, budgets, risks, dependencies, and resource allocation.
- Establish delivery governance and ensure projects meet quality, schedule, and business objectives.
- Drive delivery planning, status reporting, issue resolution, and executive communication.

Team Leadership & People Management

- Lead, mentor, and develop a team of Data Engineers and Technical Leads.
- Drive workforce planning, onboarding, capability development, and succession planning.
- Establish performance expectations and promote engineering excellence.
- Foster a culture of accountability, collaboration, continuous improvement, and innovation.

Data Platform & Engineering Governance

- Govern the implementation and support of enterprise data platforms, data lakes, Lakehouse architectures, and analytics solutions.
- Ensure adherence to architecture standards, security policies, development guidelines, and operational processes.
- Lead architecture and design review processes to ensure solution quality and compliance.
- Drive standardization, reuse, automation, and operational efficiency across the data ecosystem.

Stakeholder & Business Engagement





- Partner with business leaders, product owners, enterprise architects, and technology teams to define priorities and delivery roadmaps.
- Translate business objectives into executable delivery plans.
- Manage stakeholder expectations and ensure alignment between business outcomes and technical solutions.
- Provide regular updates to leadership on delivery status, risks, and strategic initiatives.

Data Quality, Compliance & Risk Management

- Ensure implementation of data governance, security, privacy, and compliance requirements.
- Establish controls for data quality, monitoring, and operational readiness.
- Identify delivery risks and implement mitigation plans proactively.

Analytics & AI Enablement

- Enable enterprise reporting and analytics through optimized data products.
- Support advanced analytics, machine learning, and AI initiatives by providing trusted and scalable data foundations.
- Evaluate and adopt emerging technologies that improve engineering efficiency and business value.
- - Solid understanding of:
- Azure Data Platform
- Databricks
- Azure Data Factory (ADF)
- PySpark
- SQL
- Lakehouse/Data Lake architectures
- Data Governance and Data Quality frameworks

📌 Tpm Manager (Hyderabad)
🏢 Affine Analytics
📍 Hyderabad