Senior Databricks Engineer

DataBeat; Hyderabad; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

DataBeat is seeking an experienced Senior Databricks Engineer to lead enterprise data engineering across Azure and AWS. You will architect, build, and optimize lakehouse platforms, mentor teams, and interact with clients and stakeholders to translate requirements into scalable, secure solutions.

The role demands 8+ years in data engineering, deep Databricks expertise, and strong delivery of end-to-end projects, including CI/CD, governance, and performance tuning for large-scale analytics

Qualifications

• 8+ years in Data Engineering, Big Data, and Analytics.
• Minimum 5+ years hands-on with Databricks, Spark, PySpark, and SQL.
• Experience designing enterprise Data Lake, Lakehouse, and Data Warehouse solutions.
• Experience with Azure/AWS data services and CI/CD pipelines.

Responsibilities

• Lead end-to-end data engineering projects using Databricks and Delta Lake.
• Own requirement gathering, design, development, testing, deployment, and production support.
• Collaborate with clients and stakeholders to translate requirements into scalable technical solutions.
• Mentor junior and mid-level engineers and drive governance and best practices.
• Design scalable Lakehouse architectures across Azure and AWS and optimize pipelines.

Skills

Technical leadership

Stakeholder management

Solution design

Mentoring teams

Education

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

Tools

Databricks

PySpark

Apache Spark

Delta Lake

Azure Data Factory

Azure Synapse Analytics

AWS S3

Glue

Unity Catalog

MLflow

CI/CD Pipelines

GitLab

GitHub

Power BI

Tableau

Job description

Role Summary

We are seeking an experienced Senior Databricks Developer with 8+ years of experience in Data Engineering, Big Data, and Cloud Analytics solutions, including extensive hands-onexpertise in Databricks, Apache Spark, PySpark, SQL, and Delta Lake. The ideal candidate will be responsible for leading end-to-end data engineering projects, engaging directly with clients and business stakeholders, mentoring development teams, and delivering scalable, secure, and high-performance data platforms across Azure and AWS environments.

Job Title: Senior Databricks Engineer

Experience Required: 8+ Years

Role Summary

We are seeking an experienced Senior Databricks Developer with 8+ years of experience in Data Engineering, Big Data, and Cloud Analytics solutions, including extensive hands-onexpertise in Databricks, Apache Spark, PySpark, SQL, and Delta Lake. The ideal candidate will be responsible for leading end-to-end data engineering projects, engaging directly with clients and business stakeholders, mentoring development teams, and delivering scalable, secure, and high-performance data platforms across Azure and AWS environments. This role requires strong technical leadership, solution design capabilities, stakeholder management skills, and the ability to drive data transformation initiatives from requirements gathering through deployment and production support.

Technical Expertise

Databricks (PySpark, SQL, Notebooks, Workflows), Apache Spark, Delta Lake, Python, Azure Data Factory (ADF), Azure Synapse Analytics, AWS S3, Glue, Lambda, Unity Catalog MLflow, Databricks Job Clusters, CI/CD Pipelines, GitLab / GitHub, Data Governance & Data Quality Frameworks, Power BI / Tableau, Data Cataloging, Lakehouse Architecture, Medallion Architecture, Performance Tuning & Optimization

Key Responsibilities

• Lead the design, development, and implementation of enterprise-scale data engineering solutions using Databricks, PySpark, SQL, and Delta Lake.
• Own end-to-end project delivery, including requirement gathering, solution design, development, testing, deployment, and production support.
• Collaborate directly with clients, business stakeholders, architects, and product owners to understand business requirements and translate them into scalable technical solutions.
• Conduct client discussions, solution workshops, effort estimations, technical presentations, and architecture reviews.
• Design and implement scalable Lakehouse architectures and data platforms across Azure and AWS cloud environments.
• Lead the development of high-performance ETL/ELT pipelines supporting both batch and real-time data processing workloads.
• Drive best practices around coding standards, architecture governance, version control, CI/CD implementation, and operational excellence.
• Architect and optimize Databricks Workflows, Job Clusters, Delta Tables, and Spark applications to maximize performance and minimize infrastructure costs.
• Implement data governance frameworks using Unity Catalog, ensuring proper access controls, lineage tracking, metadata management, and compliance standards.
• Mentor and guide junior and mid-level data engineers through code reviews, technical coaching, and knowledge-sharing initiatives.
• Lead technical teams and coordinate project activities to ensure timely and successful project delivery.
• Collaborate with Data Scientists, BI Teams, and Analytics stakeholders to enable advanced analytics and machine learning use cases.
• Drive automation initiatives through Infrastructure as Code (IaC), DevOps practices, and CI/CD pipelines.
• Establish monitoring, observability, and performance tracking frameworks for data platforms and pipelines.
• Ensure security, compliance, data quality, and operational reliability across enterprise data ecosystems.
• Prepare and maintain technical architecture documents, design specifications, implementation guides, and operational runbooks.

Requirements

• 8+ years of experience in Data Engineering, Big Data, and Analytics platforms.
• Minimum 5+ years of hands-on experience working with Databricks, Apache Spark, PySpark, and SQL.
• Strong expertise in designing and implementing enterprise-scale Data Lake, Lakehouse, and Data Warehouse solutions.
• Deep understanding of Spark internals, cluster management, performance tuning, partitioning strategies, and resource optimization.
• Extensive experience working with Delta Lake, schema evolution, ACID transactions, and large-scale distributed data processing.
• Hands-on experience integrating Databricks with Azure (ADF, Synapse) and/or AWS (S3, Glue, Lambda) services.
• Proven experience handling end-to-end project delivery and managing technical engagements with clients and stakeholders.
• Experience leading development teams and mentoring engineers in enterprise environments.
• Strong understanding of data modeling, dimensional modeling, Medallion Architecture, and modern data platform design principles.
• Expertise in implementing CI/CD pipelines, DevOps practices, and automated deployment strategies.
• Experience with Unity Catalog or equivalent governance platforms.
• Excellent communication, stakeholder management, presentation, and client-facing skills.
• Ability to lead technical discussions, architecture reviews, and solution design workshops.
• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.

Information Security & ISO 27001 Compliance

Security is at the heart of everything we do. In this role, you will be strictly required to uphold our Information Security Management System (ISMS) policies in alignment with ISO/IEC 27001 standards. Responsibilities include safeguarding sensitive asset data, completing mandatory security awareness training, reporting potential security incidents or vulnerabilities immediately, and ensuring that daily operations comply with our rigorous data protection protocols.