Data Engineering Manager - Databricks And Lakehouse

Unison Group; Bengaluru; On-site; INR 3,200,000 - 5,600,000; Full time

Job summary

Unison Group in Bengaluru, India is seeking an experienced Data Engineering Manager to lead the design, development and operation of scalable data solutions. You will drive Databricks-based lakehouse architectures, oversee a team of data engineers, and partner with analytics, security and platform groups to deliver high-quality data products.

You will champion best practices, governance and automation across pipelines, ensuring secure, cost-efficient and reliable data delivery.

Qualifications

• Bachelors or Masters in CS/Engineering/IT/Data Science or related field.
• Significant data engineering leadership experience.
• Strong hands-on Databricks and lakehouse architecture knowledge.
• Proficiency with Spark/PySpark, SQL, Python and Delta Lake.
• Experience implementing CI/CD, automated testing, logging and monitoring.
• Knowledge of data governance, security, privacy and RBAC.
• Excellent stakeholder management and communication skills.

Responsibilities

• Lead and mentor a team of data engineers; set technical direction.
• Design and operate scalable data pipelines and Lakehouse solutions.
• Define standards for ingestion, transformation, orchestration and deployment.
• Collaborate with business, analytics, data science and security teams.
• Promote reusable, metadata-driven frameworks and Medallion Architecture patterns.
• Embed data quality, governance and privacy controls across pipelines.
• Review designs, code and deployment approaches for reliability and maintainability.
• Optimize Databricks workloads for performance and cost efficiency.
• Support Agile delivery with backlog grooming and sprint planning.

Skills

Leadership

People management

Stakeholder management

Problem-solving

Written communication

Verbal communication

Education

Bachelor's or Master's in Computer Science / Engineering / IT / Data Science

Tools

Databricks

Azure Databricks

Delta Lake

Apache Spark / PySpark

SQL

Python

CI/CD

Azure DevOps

Git

Unity Catalog

Job description

Job Description:

Role Summary

We are seeking an experienced Data Engineering Manager with strong Databricks and modern cloud data engineering expertise to lead the design, development and operation of scalable enterprise data solutions. The role combines technical leadership, people management, architecture oversight and delivery accountability. The successful candidate will establish engineering standards, reusable frameworks and robust practices for secure, governed, reliable and cost-efficient Lakehouse solutions.

Key Responsibilities

Lead, mentor and support a team of data engineers, setting technical direction and encouraging engineering best practices.

Design, build and operate scalable data pipelines and Lakehouse solutions using Databricks, Apache Spark, Delta Lake, SQL, Python and cloud-native services.

Define standards for ingestion, transformation, orchestration, automated testing, deployment, observability, monitoring and production support.

Collaborate with business, analytics, data science, architecture, security and platform teams to translate requirements into high-quality data solutions.

Champion reusable and metadata-driven frameworks, automation, Medallion Architecture patterns and modern data engineering practices.

Embed data quality, security, governance, privacy and compliance controls across pipelines and data products.

Review solution designs, code and deployment approaches to maintain consistency, resilience, maintainability and operational reliability.

Optimize Databricks workloads for performance, scalability, reliability and cost efficiency.

Support Agile delivery, including backlog refinement, sprint planning, estimation, risk management, continuous improvement and technical roadmap development.

Required Qualifications & Experience

Bachelors or Masters degree in Computer Science, Engineering, Information Technology, Data Science or a related discipline.

Significant professional experience in data engineering, including experience leading or managing data engineering teams.

Strong hands-on experience with Databricks and Lakehouse-based architectures.

Advanced proficiency in Apache Spark / PySpark, SQL, Python, Delta Lake, ETL/ELT, data pipeline development and orchestration.

Strong understanding of Medallion Architecture, distributed processing and modern cloud data-platform patterns.

Experience implementing CI/CD, automated testing, logging, monitoring, alerting and controlled deployment practices.

Working knowledge of data governance, lineage, data quality, security, privacy and role-based access control.

Proven experience optimizing large-scale workloads for performance, reliability and cost.

Experience conducting design and code reviews and establishing engineering standards.

Strong stakeholder management, problem-solving and written and verbal communication skills.

Preferred Qualifications

Experience with Azure Databricks, Unity Catalog and the broader Azure data ecosystem.

Experience building reusable, configuration-driven or metadata-driven ingestion and transformation frameworks.

Exposure to Azure DevOps, Git-based CI/CD, infrastructure as code and automated release controls.