Senior Databricks Engineer

Experience Required: 8+ Years

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.

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

• 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.

• 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.