Ekfrazo Technologies - Senior Data Engineer

Description :

Role : Senior Data Engineer - Databricks / Master Data

Experience : 6+ Years

Work Type : Full-Time, Remote

Shift Timing : 4 :30 PM IST - 12 :30 AM IST

Contract Duration : 12 Months+

Start Date : February 2026

Role Overview :

- Design, build, and maintain scalable data engineering solutions for master data initiatives

- Lead development on Databricks-based platforms using modern data engineering practices

- Ensure reliable, high-performance data pipelines supporting analytics and business use cases

Key Responsibilities :

- Design, develop, and optimize data pipelines using Databricks, PySpark, Python, and SQL

- Implement and manage master data processing and transformation workflows

- Build and orchestrate workflows using Apache Airflow

- Ensure data quality, consistency, and reliability across pipelines

- Optimize performance of large-scale data processing jobs

- Integrate data from multiple structured and semi-structured sources

- Implement best practices for data governance and security

- Collaborate with analytics, platform, and business teams

- Troubleshoot data pipeline failures and performance issues

- Document data models, workflows, and technical solutions

Key Result Areas (KRAs) :

- Stable and scalable Databricks data pipelines delivered on time

- High data accuracy and consistency for master data domains

- Improved pipeline performance and reduced processing latency

- Minimal pipeline failures and faster incident resolution

- Effective workflow orchestration and automation

- Strong collaboration and technical ownership of data solutions

Required Experience & Qualifications :

- 6- 9 years of experience in data engineering roles

- Strong hands-on expertise in Databricks, PySpark, Python, and SQL

- Minimum 4 years of experience building and maintaining data pipelines

- Minimum 4 years of experience with Apache Airflow

- Proven experience working with AWS data services

Skill Sets :

- Databricks platform development and optimization

- Advanced PySpark and SQL for large-scale data processing

- Python for data engineering and automation

- Apache Airflow for workflow orchestration

- AWS services including S3, Athena, EMR, Redshift, Glue, and Lake Formation

- Data pipeline design, performance tuning, and monitoring

- Master data management concepts and best practices

- Strong problem-solving and debugging skills

- Ability to work independently in a remote, distributed team environment

- Clear communication and documentation skills