Company Overview
DigitalXnode works with organizations across India to address their technology and workforce requirements. We help businesses find professionals whose skills and experience align with specific roles, projects, and engagement needs. Through recruitment and staff augmentation services, we aim to create the right connections between businesses seeking talent and professionals looking for relevant career opportunities.
Job Summary
We are looking for an experienced Databricks Engineer / Lead to provide deep technical expertise and delivery leadership for modern data-platform initiatives. The role focuses on designing and implementing scalable, cost-efficient data platforms using Databricks and building modern lakehouse architectures that support advanced analytics, AI, and business intelligence use cases.
Key Responsibilities
- Provide technical expertise and delivery leadership for Databricks-based data platform initiatives.
- Design and implement scalable and cost-efficient data platforms using Databricks.
- Build and evolve modern lakehouse architectures for analytics, AI, and business intelligence workloads.
- Develop data engineering solutions using PySpark, Python, and Scala.
- Work with Databricks notebooks and platform capabilities to develop and operationalize data solutions.
- Work with Unity Catalog and Lakeflow capabilities for data governance and data engineering workflows.
- Configure and optimize Databricks clusters based on workload and performance requirements.
- Apply Data Vault concepts where appropriate to support enterprise data-platform requirements.
- Collaborate with technical and business stakeholders to understand data requirements and translate them into scalable solutions.
- Provide technical guidance to engineering teams and contribute to delivery planning and implementation.
- Support platform optimization with attention to performance, scalability, reliability, and cost efficiency.
Required Technical Skills
- 10–14 years of overall professional experience.
- Strong hands-on experience with Databricks data engineering and lakehouse platforms.
- Strong PySpark experience.
- Strong Python programming skills.
- Working experience with Scala for data engineering workloads.
- Experience with Databricks notebooks and cluster configuration.
- Knowledge of Unity Catalog and Lakeflow.
- Experience designing and implementing lakehouse architectures.
- Understanding of Data Vault concepts and their application in enterprise data platforms.
- Ability to design scalable and cost-efficient data solutions.
- Strong technical problem-solving and delivery skills.
Preferred Skills
- Experience leading Databricks engineering or data-platform initiatives.
- Experience supporting advanced analytics, AI, and business intelligence use cases.
- Experience with enterprise data architecture and modern lakehouse patterns.
- Strong understanding of Databricks platform capabilities and optimization.
- Experience working in Financial Services or other data-intensive enterprise environments.
- Ability to provide technical leadership and guide engineering teams through delivery.
AI Experience
The role supports data platforms for advanced analytics and AI use cases. Direct AI/ML development experience is not specified in the supplied requirements, but exposure to data platforms supporting AI workloads is relevant.
Managerial Experience
The role includes delivery leadership and technical guidance. Direct people-management responsibility is not specified.
Operational Experience
Experience designing, implementing, configuring, and supporting Databricks-based data platforms, including notebooks, lakehouse architecture, cluster configuration, governance, and data engineering workflows.
Qualifications
UG: Any Graduate.
Certifications
Preferred certifications include Databricks Certified Data Engineer Associate and Databricks Certified Data Engineer Professional. Certifications are preferred but not mandatory.
Experience
10–14 years of relevant professional experience.
Submit Resume at apply@digitalxnode.com
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