Databricks Engineer

Why Build Your Career at NICE?

At NICE, careers are built with intention combining cutting-edge

technology, continuous learning, and global exposure.

Impactful Innovation

Design and deliver enterprise-grade

Data Engineering, Analytics, BI

Reporting, and AI solutions that

power real-world decision

intelligence across industries.

Structured Career Growth

Role-based growth paths, certifications, leadership programs, and continuous upskilling.

Certification reimbursement programs

Planned progression, not guesswork

Global Client Exposure

Work with 100+ global clients across India, Middle East, USA, and beyond spanning BFSI, Retail, Media, Automotive, and Life Sciences.

On-Site & Consulting Opportunities

Gain hands-on exposure at client locations to strengthen consulting, communication, and solution architecture skills. Additionally, contribute to Centers of Excellence (CoEs) and innovation initiatives.

Empowered Work Culture

A collaborative, inclusive environment where ownership is encouraged and ideas are valued:

Mentorship from senior architects & practitioners

Flat, transparent communication

Rewards & Recognition

Spot awards, peer recognition, performance bonuses, and milestone celebrations that acknowledge impact—not just tenure.

A Vibrant Professional Community

Hackathons, CSR initiatives, sports, learning forums, and team celebrations that foster belonging and collaboration.

Perks & Benefits

Benefits That Support Your Professional and Personal Life

Fitness & wellness partnerships

Local restaurant & lifestyle tie-ups

Clearly defined career progression paths

Upskilling & Cross-skilling programs

Flexible Work Hours

Sustainable work–life balance

Health & accident insurance

Upskilling & Cross-skilling programs

Databricks Engineer

• FullTime
• EXP : 8+ Years
• Pune / Nagpur , India

Job Summary

We are seeking an experienced Data Engineer with strong hands-on expertise in Databricks on any cloud platform (AWS, Azure, or GCP), along with proven skills in SQL, Python, and PySpark. The ideal candidate will have a solid background in database design, data processing, and building scalable data pipelines in a cloud-based environment.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes using Databricks and PySpark
• Work with structured and semi-structured data across various cloud platforms (AWS, Azure, or GCP)
• Write optimized and complex SQL queries for data extraction and transformation
• Implement data ingestion from various sources into the data lake/warehouse
• Collaborate with data analysts, business stakeholders, and other engineering teams to understand requirements and deliver solutions
• Monitor and improve the performance of existing data pipelines
• Ensure data quality, security, and governance across the data lifecycle

Required Skills & Qualifications:

• 5–7 years of professional experience in Data Engineering or related roles
• Strong experience with Databricks on any cloud platform (AWS, Azure, or GCP)
• Proficiency in SQL, Python, and PySpark
• Solid understanding of database structures, data modeling, and data warehousing concepts
• Experience with cloud data services and storage solutions
• Familiarity with CI/CD practices and version control tools like Git
• Excellent problem-solving and communication skills

Good to Have

• Exposure to Delta Lake, Lakehouse architecture, or MLflow
• Knowledge of Apache Airflow or other workflow orchestration tools
• Experience in performance tuning and job optimization in Spark environments

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