Senior Software Engineer – Databricks Platform

Overview

Hyderabad, India

Experience: 6–10 Years

Company: Anblicks

About Anblicks

Anblicks is a cloud data engineering and analytics company helping enterprises modernize their data platforms through Cloud, Data Engineering, AI/ML, and Advanced Analytics solutions. We specialize in building scalable, secure, and high-performance data ecosystems that power enterprise decision-making.

We are seeking a highly skilled Senior Software Engineer – Databricks Platform to design and build enterprise-grade, production-ready data applications on Databricks. This is a hands-on technical role requiring deep platform expertise, ownership mindset, and strong collaboration skills.

Role Overview

This role focuses on designing, developing, and operating scalable data-intensive systems on the Databricks Lakehouse Platform. You will work closely with Architects, Data Engineers, Analytics teams, and client stakeholders to deliver secure, high-performance, and cost-optimized solutions.

This is ideal for senior engineers who can handle ambiguous requirements, architect end-to-end solutions, and take ownership of production systems.

Key Responsibilities

• Databricks Platform Engineering
• • Design, develop, and maintain production-grade applications and data pipelines on Databricks.
  • Build and optimize stored procedures, notebooks, and UDFs using Java and Python.
  • Write efficient, well-structured SQL for analytics, transformations, and reporting.
  • Develop scalable Spark-based processing frameworks for batch and streaming workloads.
  • Leverage Delta Lake for transactional reliability and performance optimization.
• Data Governance & Secure Sharing
• • Implement and manage data governance using Unity Catalog, including permissions, lineage, and data discovery.
  • Design and support Delta Sharing solutions for secure internal and external data collaboration.
  • Build and enhance capabilities in Databricks Clean Room environments.
  • Ensure compliance with enterprise data security and governance standards.
• Performance & Cost Optimization
• • Leverage Databricks Serverless capabilities to optimize cost, scalability, and performance.
  • Tune Spark jobs and optimize query performance for large-scale data processing.
  • Implement monitoring, logging, and observability best practices.
• Architecture & Ownership
• • Translate business requirements into scalable technical designs.
  • Own features and systems end-to-end (design, implementation, testing, deployment, and operational support).
  • Participate in architecture reviews and engineering best practices.
  • Improve reliability, scalability, and resilience of data systems.
• Collaboration & Leadership
• • Collaborate with cross-functional teams including Data Engineering, Analytics, DevOps, and client stakeholders.
  • Mentor junior engineers and provide technical guidance.
  • Contribute to coding standards, documentation, and reusable frameworks.
    

• • 6–10 years of professional software engineering experience.
  • 3+ years of hands-on Databricks experience in production environments.
  • Strong proficiency in Java, Python, and SQL.
  • Hands-on experience with:
  • Apache Spark
  • Delta Lake
  • Unity Catalog (governance, permissions, lineage)
  • Delta Sharing
  • Databricks Serverless
  • Strong understanding of distributed systems and large-scale data processing.
  • Experience designing and optimizing enterprise-grade data pipelines.
  • Strong communication skills with the ability to explain technical concepts to both technical and business stakeholders.
  • Demonstrated ownership mindset and ability to drive work independently.
    

• • Experience with cloud platforms (AWS, Azure, or GCP) in a Databricks environment.
  • Familiarity with CI/CD pipelines for data and application workflows.
  • Experience implementing data governance, security, and compliance controls.
  • Experience supporting multi-tenant or client-facing data platforms.
  • Exposure to cost optimization strategies for large-scale data workloads.
  • Databricks certification (preferred).
    

• • Experience leading enterprise data modernization initiatives.
  • Strong architectural thinking with practical implementation skills.
  • Experience building reusable frameworks and platform capabilities.
  • Ability to operate in high-visibility, client-facing engagements.
  • Passion for building scalable, secure, and performant data systems.