Overview

📋 Job Details at a Glance 📍 Location Bengaluru, India 🏢 Company Fractal Analytics 👥 Experience 4-8 years 🎓 Qualification 4–8 years 📅 Eligible Batch 2023, 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Technology 🛠 Key Skills PySpark SQL AWS Glue Athena Redshift Airflow Informatica PowerCenter PostgreSQL Data Engineer

Responsibilities

• AWS at Fractal Analytics — Full Details & How to Apply Fractal Analytics is hiring for a Data Engineer
• AWS position in Bengaluru, India , requiring candidates with 4–8 years of hands-on experience in building scalable data pipelines using AWS tools. This role is part of Data Engineer
• AWS jobs in Bengaluru, India, where technical precision in data flow design is essential for operational efficiency. This Data Engineer
• This role is intended for candidates with proven experience in data pipeline development and database management. Applicants will gain practical experience with PySpark , SQL , AWS Glue , Athena , Redshift , Airflow , Informatica PowerCenter , and PostgreSQL
• AWS jobs through Fractal Analytics recruitment
• Job Role & Responsibilities The Data Engineer
• AWS at Fractal Analytics designs and implements cloud-based data pipelines to support real-time analytics, ensuring data integrity , performance , and scalability across enterprise workloads using AWS and Redshift
• This role directly enables data-driven decision-making through reliable, automated data flows. Design scalable data pipelines using PySpark and AWS Glue to process petabyte-scale datasets with 99.9% uptime and end-to-end latency under 10 minutes
• Develop ETL workflows in Informatica PowerCenter to extract, transform, and load data from source systems into PostgreSQL and Redshift with zero data duplication
• Implement SQL scripts to query Redshift and PostgreSQL databases, extracting metrics such as daily active users and conversion rates with sub-second response time
• Optimize Redshift and PostgreSQL clusters using query tuning and indexing to reduce query execution time by 30% and maintain 99.9% availability. Configure AWS Glue jobs and Athena queries to enable on-demand data access and reduce cost-per-query by 25% in production environments. Deploy automated data workflows using Apache Airflow with error handling and retry logic to ensure pipeline reliability and failure recovery within 5 minutes
• Document data processing steps, schema changes, and performance improvements in Confluence or Notion with versioned records and audit trails for compliance. Diagnose data quality issues using Redshift and PostgreSQL logs and SQL error reports to resolve anomalies and maintain data consistency across daily batch runs
• This role demands direct ownership of data pipeline performance, where every metric , query , and deployment has measurable impact on business outcomes and operational efficiency
• Required Skills & Technical Competencies The Data Engineer
• AWS Glue — intermediate to advanced — used to build and manage ETL jobs in AWS environments, enabling seamless data movement between source systems and Redshift
• Athena — intermediate — leveraged to run serverless queries on Parquet and CSV files stored in S3 , reducing data access latency and cost
• Redshift — advanced — used to design, manage, and optimize columnar databases for high-performance analytics and large-scale reporting
• PostgreSQL — intermediate to advanced — used for real-time data ingestion, schema design, and transactional data integrity in ETL processes via Informatica PowerCenter
• Informatica PowerCenter — intermediate — used to design and execute ETL workflows for data movement between source systems and PostgreSQL and Redshift with data validation rules. Apache Airflow — intermediate — used to orchestrate data pipelines with task scheduling , error handling , and monitoring for daily batch runs
• When preparing your resume, emphasize specific projects using PySpark , SQL , and Redshift with measurable performance gains and real-world data volume metrics. Eligibility Criteria This role is designed for candidates with a degree in Computer Science, Data Science, or a related field and 4–8 years of hands-on experience in data engineering or data pipeline development. Must hold a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related discipline
• Eligible application batches are 2023, 2024, 2025, and 2026
• Include GitHub links or project documentation for at least two end-to-end data pipeline implementations. Pro tip: Focus on a project where you used PySpark to process 10GB+ of data in Redshift or PostgreSQL with query optimization and performance metrics — this directly aligns with the technical expectations of the Data Engineer
• AWS role at Fractal Analytics
• Salary for Data Engineer
• AWS at Fractal Analytics 💰 Compensation Not Disclosed The advertised compensation for the Data Engineer
• AWS role at Fractal Analytics is Not Disclosed
• The exact in-hand figure and any additional components are confirmed by the company during the offer or HR discussion stage. Recommended Courses & Preparation Tips for Data Engineer
• AWS role supports core data infrastructure and pipeline development within the company. The team designs, develops, and maintains scalable data pipelines using AWS technologies. Responsibilities include managing databases like Redshift and PostgreSQL , leveraging PySpark and SQL , and working with tools such as AWS Glue , Athena , and Airflow
• Role
• Salary