# Databricks Data Specialist - R01569707 at Brillio

Databricks Data Specialist - R01569707 at Brillio in Bangalore, Karnataka, India. Hybrid. Posted August 10, 2026.

- Company: Brillio
- Location: Bangalore, Karnataka, India
- Workplace: Hybrid
- Posted: 2026-08-10
- Apply: https://jobs.lever.co/brillio-2/242c6a24-1116-4524-ae0d-bbaef31d5577/apply
- Source: https://jobmagic.ai/jobs/databricks-data-specialist-r01569707-brillio-r0gm5a

## Requirements

- Databricks Engineering: Lead Data Engineer

## Description

**Data Specialist**

### Primary Skills

Databricks Engineer

### Role Overview

We are seeking a highly skilled **Databricks Engineer** to design, develop, and optimize scalable data engineering and analytics solutions on the **Databricks Lakehouse Platform**. The ideal candidate will possess strong expertise in **Databricks, PySpark, and SQL**, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.

### Key Responsibilities

- Design, develop, and maintain end-to-end data pipelines using **Databricks** and **PySpark**.

- Build and implement **Lakehouse architectures** utilizing Bronze, Silver, and Gold data layers.

- Develop and manage **Delta Lake** solutions with ACID transactions, schema enforcement, and data reliability features.

- Create, monitor, and optimize **Delta Live Tables (DLT)** pipelines.

- Implement scalable and efficient data ingestion processes using **Auto Loader**.

- Develop and manage real-time data processing solutions using **Structured Streaming**.

- Orchestrate, schedule, and monitor data workflows using **Databricks Workflows**.

- Design and implement Lakehouse data models to support reporting, analytics, and business intelligence requirements.

- Establish and enforce data governance, security, and access controls using **Unity Catalog**.

- Optimize Spark jobs, SQL queries, and overall platform performance to ensure efficiency and scalability.

- Collaborate with cross-functional teams, including data analysts, architects, and business stakeholders, to deliver high-quality data solutions.

### Required Skills (Must Have)

- Databricks Platform

- Delta Lake

- Delta Live Tables (DLT)

- Unity Catalog

- Databricks Workflows

- PySpark and Apache Spark

- Structured Streaming

- Auto Loader

- SQL

- Lakehouse Data Modeling

- Strong understanding of data engineering best practices and scalable data architectures

### Preferred Skills (Good to Have)

### Azure Ecosystem

- Azure Data Factory (ADF)

- Azure Synapse Analytics

- Microsoft Purview

- Microsoft Fabric

### AWS Ecosystem

- AWS Glue

- AWS Lambda

- AWS Step Functions

### Data Engineering & Integration

- Apache Airflow

- DBT

- Fivetran

- Informatica

### Streaming & Analytics

- Apache Kafka

- Power BI

### Data Governance

- Collibra

- Alation

### GCP

- BigQuery

### Qualifications

- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.

- Proven experience in designing and implementing cloud-based data engineering solutions and scalable data pipelines.

- Strong analytical, troubleshooting, and problem-solving capabilities.

- Experience working in agile and collaborative environments.

- Excellent communication and stakeholder management skills.

### Preferred Candidate Profile

- Hands-on experience with modern Lakehouse architectures and enterprise-scale data platforms.

- Strong understanding of data governance, security, and compliance frameworks.

- Experience delivering both batch and real-time data processing solutions.

- Ability to work independently while collaborating effectively across global teams.

### Key Technologies

**Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI**

### Specialization

- Databricks Engineering: Lead Data Engineer

### Job requirements

Databricks Engineer

### Role Overview

We are seeking a highly skilled **Databricks Engineer** to design, develop, and optimize scalable data engineering and analytics solutions on the **Databricks Lakehouse Platform**. The ideal candidate will possess strong expertise in **Databricks, PySpark, and SQL**, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.

### Key Responsibilities

- Design, develop, and maintain end-to-end data pipelines using **Databricks** and **PySpark**.

- Build and implement **Lakehouse architectures** utilizing Bronze, Silver, and Gold data layers.

- Develop and manage **Delta Lake** solutions with ACID transactions, schema enforcement, and data reliability features.

- Create, monitor, and optimize **Delta Live Tables (DLT)** pipelines.

- Implement scalable and efficient data ingestion processes using **Auto Loader**.

- Develop and manage real-time data processing solutions using **Structured Streaming**.

- Orchestrate, schedule, and monitor data workflows using **Databricks Workflows**.

- Design and implement Lakehouse data models to support reporting, analytics, and business intelligence requirements.

- Establish and enforce data governance, security, and access controls using **Unity Catalog**.

- Optimize Spark jobs, SQL queries, and overall platform performance to ensure efficiency and scalability.

- Collaborate with cross-functional teams, including data analysts, architects, and business stakeholders, to deliver high-quality data solutions.

### Required Skills (Must Have)

- Databricks Platform

- Delta Lake

- Delta Live Tables (DLT)

- Unity Catalog

- Databricks Workflows

- PySpark and Apache Spark

- Structured Streaming

- Auto Loader

- SQL

- Lakehouse Data Modeling

- Strong understanding of data engineering best practices and scalable data architectures

### Preferred Skills (Good to Have)

### Azure Ecosystem

- Azure Data Factory (ADF)

- Azure Synapse Analytics

- Microsoft Purview

- Microsoft Fabric

### AWS Ecosystem

- AWS Glue

- AWS Lambda

- AWS Step Functions

### Data Engineering & Integration

- Apache Airflow

- DBT

- Fivetran

- Informatica

### Streaming & Analytics

- Apache Kafka

- Power BI

### Data Governance

- Collibra

- Alation

### GCP

- BigQuery

### Qualifications

- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.

- Proven experience in designing and implementing cloud-based data engineering solutions and scalable data pipelines.

- Strong analytical, troubleshooting, and problem-solving capabilities.

- Experience working in agile and collaborative environments.

- Excellent communication and stakeholder management skills.

### Preferred Candidate Profile

- Hands-on experience with modern Lakehouse architectures and enterprise-scale data platforms.

- Strong understanding of data governance, security, and compliance frameworks.

- Experience delivering both batch and real-time data processing solutions.

- Ability to work independently while collaborating effectively across global teams.

### Key Technologies

**Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI**