Data Manager - Databricks

Unison Group; Bengaluru; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Unison Group is seeking an experienced Data Engineering Manager in Bengaluru to lead design, development, and operation of scalable data solutions. You will establish engineering standards, reusable frameworks and governance for secure, reliable Lakehouse platforms.

The role combines technical leadership, people management and architecture oversight with delivery accountability to drive cost-efficient data products and robust production systems.

Qualifications

• Bachelor's or master's degree in CS/Engineering/IT or related field.
• Significant data engineering leadership experience.
• Strong Databricks and Lakehouse architecture experience.
• Hands-on Spark, PySpark, SQL, Python, Delta Lake and ETL/ELT.

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

Skills

Leadership

Data engineering

Databricks

Apache Spark

PySpark

SQL

Python

Delta Lake

ETL/ELT

CI/CD

Data governance

Security/compliance

Architecture oversight

Education

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

Tools

Azure Databricks

Unity Catalog

Azure DevOps

Git

Infrastructure as Code

CI/CD tooling

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.

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

• Bachelor's or Master's 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
• Experience supporting production-grade data platforms and operational support models
• Understanding of dimensional modelling, enterprise data modelling and semantic or data-serving layers
• Databricks or relevant cloud certification
• Experience delivering governed data products for Power BI, analytics, AI/ML or advanced analytics