Data Engineer
First seen by Alion on Oct 9, 2026.
Role : Data Engineer
About the Role:
We are looking for an experienced Data Engineer with 7 - 12 years of hands-on experience in designing, developing, and maintaining scalable data pipelines and data platforms. The ideal candidate should have strong expertise in data engineering concepts, SQL, Python, ETL/ELT processes, and cloud-based data technologies.
Key Responsibilities:
- Design, develop, and maintain scalable and reliable data pipelines for processing large volumes of structured and unstructured data.
- Build and optimize ETL/ELT workflows to ingest, transform, and load data from multiple sources.
- Develop efficient and complex SQL queries for data extraction, transformation, validation, and analysis.
- Develop data processing solutions using Python and other relevant programming technologies.
- Design and maintain data models, data warehouses, and data marts to support business and analytical requirements.
- Work with cross-functional teams to understand business requirements and translate them into scalable data solutions.
- Implement data quality, validation, reconciliation, and monitoring processes.
- Optimize data pipelines and queries for improved performance and scalability.
- Work with cloud-based data platforms and services to build modern data engineering solutions.
- Troubleshoot data pipeline failures and production issues and perform root-cause analysis.
- Ensure data security, governance, availability, and reliability across data platforms.
- Participate in code reviews and follow established development and engineering best practices.
- Create and maintain technical documentation for data pipelines, workflows, and architecture.
- Collaborate with Data Scientists, Analysts, BI teams, and other stakeholders to enable data-driven solutions.
- Contribute to the design and implementation of scalable data architecture and engineering standards.
Required Skills:
- 7 - 12 years of relevant experience in Data Engineering.
- Strong proficiency in SQL and database concepts.
- Strong hands-on experience with Python.
- Experience building and managing ETL/ELT pipelines.
- Strong understanding of data warehousing, data modelling, and data integration.
- Experience working with large-scale data processing and distributed data systems.
- Good understanding of cloud data platforms such as AWS, Azure, or GCP.
- Experience with data orchestration/workflow tools such as Airflow or equivalent.
- Knowledge of data quality, governance, and security practices.
- Strong troubleshooting and problem-solving skills.
- Good communication and stakeholder management skills.
Tech Stack:
Data Engineering, Python, SQL, ETL/ELT, Data Pipelines, Data Warehousing, Data Modelling, Cloud, Airflow, Data Integration, Data Quality
Skills
Data Engineering, Python, SQL, ETL, Data Warehousing, Cloud, Data Integration, Apache Airflow, Data Modeling