AWS Engineer

Overview

Fractal Analytics is looking for a Data Engineer with 3–4 years of hands-on experience in AWS Databricks to design, build and maintain scalable data pipelines and data solutions within the AWS cloud environment, working closely with data scientists, analysts, architects and business stakeholders.

What you'll do

• 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 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 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.

What you'll need

• Bachelor's degree in Computer Science, Information Systems, Engineering or a related discipline.
• 3–4 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.
• Understanding of version control and CI/CD practices.
• Awareness of data security, governance and metadata management principles.
• Strong analytical, problem-solving and communication skills.

Nice to have

• Experience in building data pipelines in enterprise-scale cloud data platforms.
• Familiarity with real-time / streaming frameworks and event-driven architectures.
• 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.
• Experience with data modeling and analytics enablement.
• Exposure to DevOps and platform engineering practices.
• Certification in AWS or Databricks technologies.

Details

• Location: Bengaluru.