Sr. Data Engineer

• *Location \- Remote**

• *Shift \- 3pm to 12 am**

• *Experience \- 7\+ years**

We are looking for a highly skilled and motivated **Data Engineer** with strong expertise in **AWS data services** to join our data platform team. The ideal candidate will have hands\-on experience designing scalable **data pipelines, workflow orchestration frameworks, and large\-scale data migration solutions**.

This role will be responsible for building robust **cloud\-native data engineering solutions on AWS**, migrating datasets from legacy systems and data warehouses, and ensuring secure and efficient data processing pipelines across distributed environments.

• *Key Responsibilities**

• *AWS Data Pipeline Development**

• Design and implement **scalable ETL/ELT data pipelines** using **AWS Glue, AWS Lambda, and AWS S3**.
• Build and maintain high\-performance **data ingestion frameworks** for processing large\-scale datasets.
• Implement data pipelines for **data warehousing and analytics platforms such as AWS Redshift**.
• Optimize storage and querying strategies using **AWS S3 data lakes**.

• *Data Workflow Orchestration**

• Develop and maintain **data workflow orchestration frameworks** using tools such as **Apache Airflow or AWS Step Functions**.
• Automate complex workflows including **data ingestion, transformation, validation, and loading processes**.
• Build reusable and configurable workflows to support multiple data processing use cases.

• *Data Migration \& Integration**

• Lead **data migrations from legacy data warehouse technologies** to modern AWS data platforms.
• Perform **data migration from RDBMS systems (e.g., MySQL, SQL Server, Oracle) to AWS S3 or AWS Redshift**.
• Design scalable migration frameworks for large datasets with minimal downtime.
• Integrate data sources from enterprise applications and external systems.

• *Data Security \& Governance**

• Implement secure data pipelines using **AWS security best practices**.
• Manage access control and data governance using **AWS IAM and Lake Formation**.
• Ensure **data encryption, access management, and compliance** across all data platforms.

• *Performance Optimization \& Monitoring**

• Monitor data pipelines and troubleshoot performance issues.
• Optimize ETL workflows for scalability, reliability, and cost efficiency.
• Implement logging, monitoring, and alerting mechanisms for data pipelines.

• *Required Skills \& Qualifications (Must Have)**

• **5\+ years of experience in Data Engineering or Data Platform development**
• Strong hands\-on experience with:
• **AWS**
• **AWS Glue**
• **AWS S3**
• **AWS Lambda**
• Experience with **Data Workflow Orchestration tools** such as **Apache Airflow or AWS Step Functions**
• Experience performing **data migrations from other data warehouse technologies**
• Experience performing **data migrations from RDBMS systems to AWS S3 or AWS Redshift**
• Strong expertise in **Python and SQL** for building scalable data pipelines
• Solid understanding of **ETL/ELT concepts, data partitioning, and distributed data processing**
• Experience working with **version control systems such as GitLab or Bitbucket**
• Strong debugging, analytical thinking, and problem\-solving skills
• Basic understanding of **Object\-Oriented Programming concepts**

• *Industry Knowledge \& Experience**

• Experience building **cloud\-native data engineering solutions on AWS**
• Experience with **data warehouse architectures and large\-scale analytics platforms**
• Hands\-on experience with **data extraction, transformation, and migration frameworks**
• Experience working in **high\-volume data environments such as FinTech, analytics platforms, or enterprise data systems**

• *Good to Have Skills**

• **IBM Cognos**
• **AWS Athena**
• **AWS Lake Formation**
• **AWS Redshift**
• **AWS Glue Data Catalog**
• **AWS SageMaker**
• **AWS IAM**

• *Soft Skills**

• Strong communication skills to present technical solutions and recommendations to stakeholders
• Ability to work cross\-functionally in a **fast\-paced and evolving environment**
• Detail\-oriented with a proactive approach to identifying and solving data platform challenges
• Ability to collaborate effectively with **data scientists, analysts, and platform engineering teams**

Pay: ₹3,000,000\.00 \- ₹3,500,000\.00 per year

Application Question(s)

• What is your notice period?

Experience

• AWS: 7 years (Required)
• Step function: 5 years (Required)
• Data Engineering: 7 years (Required)

Work Location: Remote