Tower Lead

Role: Tower Lead

Experience 12-15 years Location Bangalore / Hyderabad / Chennai / Kolkata

Engagement Offshore Primary stack AWS, Databricks, DBT, Airflow

Role Summary

Seeking an experienced Data Engineering Tower Lead to own end-to-end delivery and technical leadership for Investment Group data initiatives. The role requires strong expertise in AWS, Databricks, DBT, and Airflow, with accountability for modern data platform architecture, multi-pod delivery, engineering governance, and stakeholder management.

Core Responsibilities

· Lead multiple data engineering pods and own tower-level planning, delivery, quality, risks, dependencies, and escalations.

· Define scalable AWS and Databricks architecture patterns for investment data ingestion, transformation, and curation.

· Guide enterprise DBT implementation and Airflow-based orchestration, reliability, and operational readiness.

· Govern technical designs, code reviews, testing, CI/CD, release management, security, and engineering standards.

· Drive platform performance, data quality, automation, observability, resiliency, and cost optimization.

· Engage business and technology stakeholders and mentor architects, pod leads, and engineers.

Required Experience and Skills

· 12-15 years of data engineering experience with proven technical and delivery leadership.

· Strong hands-on expertise in AWS, Databricks, DBT, and Apache Airflow.

· Experience designing and delivering cloud-native data platforms and enterprise ETL/ELT solutions.

· Expertise in Databricks performance tuning, DBT transformation frameworks, and Airflow DAG design.

· Working knowledge of Infrastructure as Code, Git-based CI/CD, automated testing, and Agile delivery.

· Strong communication, stakeholder management, problem-solving, and team leadership capabilities.

Preferred

· Asset Management or Investment Management domain experience.

· Understanding of portfolio management, investment research, risk analytics, compliance, and client reporting data.

· Exposure to Harness, Kubernetes, CloudFormation or Terraform, Astronomer, Dremio, Tableau, or Autosys.

· AWS certification and experience with AI-assisted engineering tools.