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 solid 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.

📌 Senior Data Engineer (Mumbai)
🏢 AU Small Finance Bank
📍 Mumbai