Job Profile - AWS Senior Data Engineer Experience Required – 6-8 yrs
Note - Immediate to 30 days preferred.

We are looking for a highly motivated Data Engineer with 6 years of hands-on experience in AWS Databricks to join our data platform team. The role involves working closely with data scientists, analysts, architects, and business stakeholders to design, build, and maintain scalable, high-performance data pipelines and data solutions within the AWS cloud workplace.
The ideal candidate should have strong expertise in Databricks, PySpark, SQL, Delta Lake, and AWS data services, along with a good understanding of modern data engineering practices, orchestration, and data governance.
Design, develop, test, and deploy scalable ETL/ELT pipelines using AWS Databricks, PySpark, and SQL.
Build and maintain robust data pipelines for ingesting and processing structured and unstructured data from multiple sources such as Amazon S3, Amazon RDS, APIs, and external platforms.
Implement and manage Delta Lake solutions to support both batch and streaming data processing.
Optimize Spark workloads for performance, scalability, and cost efficiency.
Ensure data quality, consistency, reliability, and integrity through validations, monitoring, exception handling, and reconciliation checks.
Collaborate with cross-functional teams including data analysts, data modelers, architects, and business stakeholders to support reporting, analytics, and downstream consumption.
Support orchestration and scheduling of pipelines using tools such as AWS Glue Workflows, Apache Airflow, or AWS Step Functions.
Participate in CI/CD implementation and code deployment processes using Git, AWS CodePipeline,



and CodeBuild.
Apply best practices related to data governance, metadata management, security, and access control.
Support production issue resolution, ad hoc data requests, and continuous improvement of the data platform.
Bachelor's degree in computer science, Information Systems, Engineering, or a related discipline.

- 5 years of experience in Data Engineering or a similar role.
- Strong hands-on experience with AWS Databricks.
- Good proficiency in PySpark and SQL for large-scale data processing.
- Experience working with Delta Lake and modern lakehouse concepts.
- Familiarity with AWS services such as Amazon S3, Amazon RDS, AWS Glue, AWS Lambda, and Amazon Redshift.
- Knowledge of batch and streaming data architectures.
- Experience with workflow orchestration, monitoring, and debugging of pipelines.
- Awareness of data security, governance, and metadata management principles.
- Experience in building data pipelines in enterprise-scale cloud data platforms.

Exposure to data quality frameworks, reconciliation processes, and operational monitoring.
Working knowledge of infrastructure automation and cloud deployment best practices.
Experience collaborating in agile delivery environments.
Attention to detail and focus on data quality
Experience with data modeling and analytics enablement
Exposure to DevOps and platform engineering practices
Certification in AWS or Databricks technologies
This role offers the opportunity to work at the forefront of cloud-based data engineering, partnering with talented data scientists, analysts, and architects to build scalable, high-impact data solutions on AWS Databricks.

📌 Data Engineers required ASAP (Bengaluru)
🏢 Fractal
📍 Bengaluru