AWS & Databricks

AWS + Databricks Ecosystem | Data Engineering Leadership |

ROLE OVERVIEW

We are looking for a Lead Data Engineer to own the design and delivery of contemporary data platforms built on AWS and Databricks. This role combines deep hands-on engineering with team leadership, covering data ingestion, transformation, and warehousing across structured and unstructured sources.

KEY RESPONSIBILITIES
- Architect and deliver end-to-end data engineering solutions on AWS and Databricks, spanning ingestion, transformation, and warehousing layers.
- Design scalable pipelines for structured and unstructured data, balancing reliability, performance, and cost efficiency.
- Lead and mentor a team of data engineers, overseeing sprint planning, code quality, and technical delivery.
- Partner with architects and business stakeholders to translate requirements into robust, production-ready designs.
- Establish and maintain standards for data quality, governance, and platform scalability.

WHAT WE'RE LOOKING FOR





MUST-HAVE SKILLS

AWS Services Hands-on expertise across core AWS services spanning compute, storage, orchestration, and security in production environments.

Databricks Platform — Deep proficiency in Databricks, including Delta Lake, Unity Catalog, cluster management, and job orchestration at scale.

Data Engineering Lifecycle — Proven ability to design and operate ingestion, transformation, and warehousing pipelines across structured and unstructured data.

Team Leadership — Experience leading and mentoring data engineering teams, managing delivery timelines, and driving technical quality.

Manufacturing Industry Knowledge — Familiarity with manufacturing industry data landscapes, processes, and common use cases.

Data Modelling — Understanding of data modelling principles, including dimensional and canonical modelling approaches.

📌 Aws Data Engineer (Bengaluru)
🏢 Tredence
📍 Bengaluru