You will be responsible for:

- Design and maintain optimal data pipeline architecture to ensure efficient, scalable, and reliable data flow across the organization.

- Assemble and integrate large, complex datasets that meet both functional and non-functional business requirements, ensuring data quality and consistency.

- Build and optimize infrastructure for extraction, transformation, and loading (ETL/ELT) of data from diverse sources using SQL, Python, distributed data processing frameworks, cloud data platforms, and cloud services (such as AWS, Azure, or GCP).

- Collaborate with cross-functional stakeholders, including Executive, Product, Data, and Design teams, to address data-related technical challenges and support their data infrastructure needs.

- Develop data tools and frameworks for analytics and data science teams to empower them in building and optimizing products that position the company as an innovative industry leader.

- Partner with data and analytics experts to continuously enhance functionality, performance, and scalability of data systems.

- Lead project and stakeholder management activities, taking full ownership of the quality, timeliness, and successful delivery of data products and solutions.

What We're Looking For

Technical Skills

- Minimum 5 years of experience in a data engineering role, with hands-on experience with distributed data processing / big data frameworks (Databricks), Python, cloud data platforms, and AWS or other cloud environments (e.g., Azure, GCP).





- Experience with workflow orchestration / scheduling platforms

- Experience working with version control systems such as GitHub, GitLab, Bitbucket, or Azure Repos.

- Experience maintaining and developing software in production environments utilizing

- CI/CD platforms such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps

- Experience with modern Python API frameworks and strong understanding of RESTful services and good API design principles.

- Knowledge of system design concepts, including designing scalable, reliable, and fault-tolerant data architectures.

- Understanding of object-oriented programming principles and design patterns.

- Strong understanding of big data / distributed systems technologies, including:

- streaming & messaging platforms
- search & indexing / log analytics engines
- structured & unstructured data
- container orchestration platforms

- Demonstrated ability to design and implement end-to-end scalable and performant data pipelines.

- Proficiency in building data transformation processes, data structures, and workload management.

- Solid ability to manipulate and extract insights from large datasets using SQL, Python, and distributed processing frameworks

Professional Skills:

- Strong analytical and problem-solving skills.

- Ability to collaborate and communicate effectively with both technical and non-technical stakeholders.

- Experience building solutions and working in Agile environments (e.g., Scrum, Kanban).

📌 Senior Software Engineer - Python, Data Engineer (Ahmedabad)
🏢 Su0026P Global Market Intelligence
📍 Ahmedabad