Data Engineer

Data Engineer (Mid-Senior) | Celebal Technologies

Experience: 3-7 Years

Celebal Technologies is looking for a skilled Data Engineer with strong expertise in building scalable data platforms, modern data pipelines, and cloud-native data solutions. The ideal candidate should have hands-on experience with Databricks, Azure, PySpark, and large-scale data processing for analytics and AI-driven workloads.

Key Responsibilities

• Design, develop, and optimize end-to-end data pipelines and ETL/ELT frameworks.
• Build scalable and reliable data solutions using Databricks and Azure services.
• Develop and maintain data models, Delta Lake implementations, and cloud data platforms.
• Enable high-quality data integration, transformation, and orchestration across multiple sources.
• Collaborate with business and technical teams to support analytics, reporting, and AI initiatives.
• Ensure data quality, governance, security, and operational excellence.

Must-Have Skills

• Strong hands-on experience with:
• Databricks
• Azure Cloud
• Python, SQL, and PySpark
• ETL/ELT Development
• Data Pipelines & Data Integration
• Data Modeling
• Delta Lake
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS)
• Experience building and maintaining cloud-based data platforms.
• Knowledge of batch and streaming data processing.
• Strong communication and stakeholder management skills.

Good-to-Have Skills

• Spark performance tuning and optimization.
• Orchestration tools such as Airflow or Databricks Workflows.
• CI/CD and DevOps practices for data engineering.
• Data governance, security, and compliance frameworks.
• Experience supporting analytics, machine learning, and AI workloads.
• Databricks Certification (Associate/Professional) is a plus.

What We're Looking For

• Strong problem-solving and analytical mindset.
• Ability to work in a fast-paced, client-facing environment.
• Passion for building reliable, scalable, and high-performance data solutions.

Interested candidates can share their profiles at:
[email removed]