Job Summary

We are seeking an experienced Senior Data Engineer to design, build, and support scalable data integration and data processing solutions across cloud-based platforms. The ideal candidate will have solid expertise in ETL/ELT development, large-scale data processing, AWS services, workflow orchestration, and modern data architecture. This role requires close collaboration with cross-functional teams to deliver reliable, high-performance data pipelines that support business intelligence, analytics, and operational data needs.

Key Responsibilities

- Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, and integration.
- Build and support data workflows across cloud-based environments and distributed data platforms.
- Develop robust data solutions capable of processing large volumes of structured and unstructured data.
- Create and optimize SQL queries, data models, and database solutions to ensure data quality and performance.
- Implement orchestration and scheduling workflows using tools such as Apache Airflow, Azure Data Factory, or AWS Step Functions.
- Design resilient and fault-tolerant data pipelines with logging, monitoring, retry mechanisms, idempotency, and recovery capabilities.
- Work with data lakes, data warehouses, and relational/non-relational databases to support enterprise analytics.
- Integrate APIs, streaming platforms, and event-driven architectures into data engineering solutions.
- Collaborate with architects, software engineers, analysts, and business stakeholders to define and deliver data requirements.
- Support DevOps practices including CI/CD pipelines, automated testing, containerization, and infrastructure-as-code.
- Participate in code reviews, troubleshooting, performance tuning, and production support activities.
- Ensure adherence to data governance, security, compliance, and quality standards.

Required Qualifications





- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical discipline. Equivalent practical experience may be considered.
- 5+ years of experience in Data Engineering, ETL/ELT development, or Data Integration.
- Strong experience designing and supporting large-scale data processing solutions in cloud or distributed environments.
- Advanced proficiency in SQL.
- Hands-on experience in at least one programming language:
- Python
- Java
- Scala
- Spark SQL

- Experience with workflow orchestration tools such as:

- Apache Airflow
- Azure Data Factory (ADF)
- AWS Step Functions

- Strong understanding of:

- Relational databases
- NoSQL databases
- Data warehouses
- Data lake architectures

- Experience implementing monitoring, logging, error handling, retry logic, and recovery processes for production data pipelines.
- Excellent analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

- Experience working with AWS cloud data platforms.
- Hands-on experience with:
- AWS Lambda
- Apache Kafka

- Knowledge of:

- Data Modeling
- Metadata Management
- Data Governance
- Master Data Management (MDM)

- Experience with:

- Docker
- Kubernetes
- CI/CD pipelines
- Infrastructure as Code (Terraform/CloudFormation)

- Experience working in regulated industries such as:

- Financial Services
- Banking
- Healthcare
- Insurance

Technical Environment

The successful candidate will work within a modern data engineering ecosystem that may include:

- AWS Cloud Services
- Data Lakes and Data Warehouses
- Distributed Compute Platforms
- Apache Kafka and Streaming Systems
- APIs and Data Integration Services
- Apache Airflow / AWS Step Functions
- Git and Source Control Management
- Automated Testing Frameworks
- Monitoring and Observability Platforms
- Docker and Containerized Deployments
- CI/CD and Infrastructure as Code Tools

📌 Aws Data Engineer (Hyderabad)
🏢 Hexaware Technologies
📍 Hyderabad