Hands-on experience with AWS services such as S3, Lambda, Glue, IAM, etc.
Strong understanding of data modeling, warehousing, and distributed systems.
Experience with version control systems (e.g., Git) and CI/CD pipelines.

Preferred Qualifications:
Experience with Databricks or similar data platforms.
Familiarity with Java for backend or data-related development.
Exposure to API development and integration with data services.

Nice to Have:
Knowledge of data lake architectures and real-time data processing.
Experience with orchestration tools like Airflow or AWS Step Functions.
Understanding of DevOps practices in data engineering contexts.As a Data Engineer youll be responsible for acquiring, curating, and publishing data for analytical or operational uses.



Data should be in a ready-to-use form that creates a single version of the truth across all data consumers, including business users, data scientists, and Technology. Ready-to-use data can be for both real time and batch data processes and may include unstructured data. Successful data engineers have the skills typically required for the full lifecycle software engineering development from translating requirements into design, development, testing, deployment, and production maintenance tasks. You’ll have the chance to work with various technologies from big data, relational and SQL databases, unstructured data technology, and programming languages

📌 Data Designer (Hyderabad)
🏢 Tekskills
📍 Hyderabad