Build, develop, and optimize high-capacity data workflows using Databricks (Delta Lake, Spark).
Build and maintain batch and real-time processing pipelines on cloud platforms.
Implement data models, transformations, and performance optimizations for large-scale datasets.
Ensure data accuracy, management, and dependability in production systems.
Act as a technical lead for small to mid-sized teams, driving build discussions, code reviews, and engineering guidelines.
Own end-to-end delivery of data solutions from ingestion to transformation and BI/visualization (Power BI/Tableau).
Be responsible for the design and implementation of data models optimized for analytics and reporting (star/snowflake schemas).
Mentor junior engineers and BI developers, ensuring high-quality, scalable, and user-friendly work.
Work directly with clients to understand requirements and translate them into solutions.
Lead technical discussions, solution walkthroughs, and architecture reviews.
Requirements
6-9 years of practical experience in data engineering or analytics roles.
At least 3 years of practical experience working with Databricks.
Strong expertise in Apache Spark ( PySpark ), Delta Lake, SQL, and Python.
Experience working on at least one hyperscaler : AWS (preferred: S3, Glue, Lambda, IAM, EC2) OR Azure / GCP.
Demonstrated experience crafting and implementing end-to-end data pipelines.
Exposure to AI/ML or GenAI concepts (RAG, LLMs, or model integration, Mosaic AI / DBRX).
Experience in client-facing roles with strong interpersonal skills.
Familiarity with modern data architecture models (Lakehouse, Medallion architecture).
Familiarity with CI/CD, DevOps, and data pipeline orchestration.
Knowledge of data governance and security frameworks.
Future-Ready Skills (Nice to Have):
Experience with other data engineering tools and technologies.
Advanced certifications in data engineering or cloud technologies.
Knowledge of new AI/ML technologies and how they apply to data engineering.
Strong problem-solving abilities and proactive approach.
Benefits
We offer a comprehensive benefits package including Medical Insurance, PF, Gratuity, paid holidays, and more.We are an equal opportunity employer
Additional Information
As a Senior Data Engineer at OneMagnify, you will be at the forefront of our Data & Analytics practice. You will lead the development and delivery of scalable data platforms and AI-powered solutions, translating business requirements into production-grade data pipelines. Your role will be essential in enabling advanced analytics and integrating AI/GenAI capabilities into enterprise data ecosystems, ensuring flawless execution and delivery.
The OneMagnify team is looking for a Senior Data Engineer who will help to develop, enhance, and improve scalable data pipelines by using Databricks and cloud platforms. OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets.
Role Summary
As a Senior Data Engineer at OneMagnify , you will be at the forefront of our Data & Analytics practice. You will lead the development and delivery of scalable data platforms and AI-powered solutions, translating business requirements into production-grade data pipelines. Your role will be essential in enabling advanced analytics and integrating AI/GenAI capabilities into enterprise data ecosystems, ensuring flawless execution and delivery.
The OneMagnify team is looking for a Senior Data Engineer who will help to develop, enhance, and improve scalable data pipelines by using Databricks and cloud platforms.
The Impact You'll Have:
Motivated to advance innovation and excellence in data engineering.
Exceptional attention and diligence for data quality, governance, and reliability.
A deep understanding of modern data architecture patterns, ensuring alignment to standard methodologies.
Ability to develop and implement high-quality data solutions using advanced technologies.