Data Engineer

Sourcebae

Pune District

Hybrid

INR 2,200,000 - 3,800,000

Full time

14 days+

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Job summary

A leading IT solutions provider is seeking a Senior Python Data Engineer in Pune, Maharashtra. The role requires designing and building enterprise-level data systems and managing scalable data pipelines. Candidates should have 6-10 years of experience in software/data engineering, particularly in Python, PySpark, and Azure Data technologies. The position starts onsite during training, transitioning to a hybrid work model.

Qualifications

6-10 years of experience in software or data engineering.
Advanced level proficiency in Python and expert-level PySpark experience.
Mandatory expertise in Databricks and Azure Data Factory (ADF).
Strong command over SQL for complex datasets.
Solid understanding of data structures, design patterns, and scalable architectures.
Cloud exposure: Azure, AWS, or GCP.

Responsibilities

Design and maintain data pipelines using Python and PySpark.
Build data solutions from scratch ensuring clean code.
Utilize Databricks and Azure Data Factory for data orchestration.
Optimize complex SQL queries for large datasets.
Develop reusable frameworks and design patterns for scalability and performance.
Collaborate with cross-functional teams to translate business requirements into technical solutions.
Drive code reviews, performance tuning, and deployment automation.

Skills

Python programming

PySpark

Databricks

Azure Data Factory

SQL

Cloud platforms

Databricks

Azure Data Factory

Problem solving

Tools

Databricks

Azure Data Factory

Job description

Sr. Talent Acquisition Specialist | Specialized in AI, Cloud & Core Tech Hiring | Building Future-Ready, High-Impact Teams

Note :- Below 5 Years of candidate should not apply for the same not even 4.5/4.11

About the Role

Join a fast-paced, innovation-driven IT solutions provider to design and build our next-generation, enterprise-level data systems. We are seeking an expert Senior Python Data Engineer to take ownership of end-to-end data solutions, utilizing the modern Azure Data Stack. You'll have the freedom to build from the ground up, influence architecture, and drive clean engineering principles.

Experience: 6 - 10 Years (Preferably 8+ years of hands‑on experience)

Work Mode: Onsite during initial training period, transitioning to Hybrid post‑training.

What You Will Do

Design, develop, and maintain highly scalable data pipelines and applications using Python and PySpark.
Build end-to-end data solutions from scratch, ensuring clean, modular, and reusable code.
Utilize Databricks and Azure Data Factory (ADF) for robust data workflow orchestration, automation, and monitoring.
Write and optimize complex SQL queries for processing, transformation, and validation of large-scale datasets.
Develop dynamic, reusable frameworks and implement design patterns for system scalability and performance.
Collaborate with cross‑functional teams to translate complex business requirements into high‑quality technical solutions.
Drive best practices in code reviews, performance tuning, and deployment automation.

What We're Looking For (Must‑Have Skills)

Core Experience: 6-10+ years in software or data engineering, with a strong focus on building data platforms.
Programming: Advanced level proficiency in Python coding and scripting, expert‑level hands‑on experience with PySpark.
Data Stack: Mandatory expertise in Databricks and Azure Data Factory (ADF).
Database: Strong command over SQL for working with large, complex datasets.
Architecture: Solid understanding of data structures, design patterns, and scalable architectures.
Cloud: Exposure to cloud platforms such as Azure, AWS, or GCP.
A problem‑solver mindset with the ability to think innovatively and deliver end‑to‑end solutions.