What you will do

Data Engineering & Platform Development

- Design, develop, and maintain scalable batch and real-time data pipelines.

- Build and optimize ETL/ELT workflows using modern data engineering frameworks.

- Develop and manage data lake, data warehouse, lake house architecture and snowflakes.

- Implement data quality checks, validation frameworks, and monitoring solutions.

- Optimize data processing jobs for performance, scalability, and cost efficiency.

- Collaborate with analytics, BI, and AI teams to deliver trusted datasets.

Cloud & Infrastructure

- Build and maintain cloud-native data platforms on AWS, Azure, or GCP.

- Implement Infrastructure as Code (IaC) using Terraform or equivalent tools.

- Support CI/CD implementation for data engineering workloads.

- Ensure security, compliance, and governance standards across data platforms.

Collaboration & Delivery

- Work directly with stakeholders to understand business requirements and translate them into technical solutions.

- Participate in architecture discussions, design reviews, and sprint planning.

- Perform code reviews and mentor junior engineers.

- Contribute to technical documentation, standards, and reusable assets.

Innovation & Practice Building

- Evaluate and recommend modern data engineering tools and frameworks.

- Contribute to internal accelerators, reusable components, and best practices.

- Support proof-of-concepts and emerging technology initiatives in analytics, AI, and data platforms.

Requirements

Must have





- 4 to 5 years of experience in Data Engineering.

- Solid expertise in Python, PySpark, and SQL.

- Hands-on experience with Spark-based data processing at production scale.

- Experience with cloud platforms such as AWS, Azure, or GCP.

- Strong understanding of Data Lakes, Data Warehouses, and Lakehouse architectures.

- Experience with orchestration tools such as Airflow, Azure Data Factory, or similar.

- Experience with data modeling, performance tuning, and pipeline optimization.

- Knowledge of CI/CD, Git, and DevOps practices.

- Strong communication and stakeholder management skills

Mandatory Certifications (Any One Required)

- Databricks Certified Data Engineer Associate

- Databricks Certified Data Engineer Professional

- AWS Certified Data Engineer – Associate

- Microsoft Certified: Azure Data Engineer Associate (DP-203)

- Google Professional Data Engine

Benefits

- Opportunity to work on enterprise-scale cloud and data engineering projects.
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Exposure to global clients and modern data platforms.
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Sponsorship for advanced cloud and data engineering certifications.
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Clear career progression toward Lead Data Engineer and Architect roles.
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Collaborative engineering culture focused on learning and innovation.
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Competitive compensation with performance-based incentives.

Date Opened

06/05/2026

Job Type

Full time

Work Experience

4-5 years

Industry

Computer

City

Ahmedabad

State/Province

Gujarat

Country

India

Zip/Postal Code

380015

📌 Senior Data Engineer (India)
🏢 Creole Studios
📍 India