Senior Data Engineer

Job Summary

We are seeking a highly skilled Senior Data Engineer with 7-10 years of experience in designing, developing, and managing enterprise-scale data platforms and data warehousing solutions. The ideal candidate will have extensive experience in building scalable ETL/ELT pipelines, architecting cloud-based data solutions on AWS, and leading teams in delivering reliable, secure, and high-performance data ecosystems.

The role requires strong expertise in Data Warehousing, Big Data technologies, AWS Data Services, Data Modeling, Performance Optimization, and People Management within a fast-paced banking and financial services environment.

Key Responsibilities

Design, develop, and maintain scalable data pipelines for batch and real-time data processing. Architect end-to-end ETL/ELT solutions for data ingestion, transformation, and consumption across enterprise systems. Build and optimize cloud-native data platforms using AWS services such as S3, EMR, Redshift, Glue, Athena, and Airflow. Define and implement enterprise data strategies, including data sourcing, data flow, storage, governance, and consumption frameworks. Collaborate with Data Analytics, Business Intelligence, Product, and Technology teams to understand and fulfill data requirements. Design and implement scalable data models supporting reporting, analytics, and business intelligence initiatives. Monitor, troubleshoot, and support production data pipelines to ensure high availability and reliability. Lead performance tuning initiatives for complex SQL queries, ETL jobs, and large-scale data processing workloads. Ensure data quality, validation, governance, security, and compliance standards are adhered to. Drive cloud cost optimization initiatives while maintaining performance and user experience. Present technical architecture, solutions, and recommendations to business and technology stakeholders. Mentor junior engineers and coordinate tasks across project teams. Prepare and maintain technical documentation, architecture diagrams, and operational runbooks.

Required Technical Skills Data Engineering & Data Warehousing

Enterprise Data Warehousing Concepts Data Lake & Data Lakehouse Architecture ETL/ELT Design and Development Data Integration and Data Migration Data Quality & Validation Frameworks

Programming & Big Data

Python Scala Apache Spark (PySpark/Spark SQL) SQL Query Optimization Distributed Data Processing

AWS Data Stack

Amazon S3 Amazon EMR Amazon Redshift AWS Glue Amazon Athena Apache Airflow IAM & AWS Security Best Practices

Data Modeling & Architecture

Dimensional Data Modeling Star Schema & Snowflake Schema Data Architecture Design Metadata Management Data Governance Frameworks

Scheduling & Orchestration

Apache Airflow Enterprise Job Scheduling Frameworks Workflow Automation

Monitoring & Production Support

Data Pipeline Monitoring Incident Management Root Cause Analysis SLA Management

Security

Data Security Principles Data Encryption & Access Controls Regulatory and Compliance Awareness

Experience Requirements

Minimum 7+ years of overall Data Engineering experience . Strong experience in Enterprise Data Warehousing (7+ years) . Hands-on expertise in building scalable ETL pipelines using Spark, Scala, and Python (7+ years) . Strong SQL development and performance tuning experience. Experience in Data Modeling, Data Architecture, and Data System Design. Extensive experience working with AWS Data Services including EMR, Redshift, S3, Athena, Glue, and Airflow. Experience supporting production environments and handling critical incidents. Exposure to banking, financial services, fintech, or large enterprise environments preferred.

Leadership & Soft Skills

Experience leading and mentoring data engineering teams. Strong stakeholder management and communication skills. Ability to present complex technical solutions to leadership and cross-functional teams. Strong analytical and problem-solving capabilities. Excellent documentation and technical writing skills. Ability to manage multiple priorities and deliver under tight timelines.

Preferred Qualifications

BE/B.Tech/M.Tech from reputed Tier-1 Institutes. AWS Certifications (Solutions Architect, Data Engineer, Developer Associate, etc.). Certifications in Spark, Big Data, or Cloud Technologies will be an added advantage.