Senior Data Engineer - ETL Pipelines
First seen by Alion on Nov 14, 2026.
About the Role:
We are looking for an experienced Senior Data Engineer with strong expertise in designing, developing, and optimizing enterprise-scale ETL/ELT pipelines and data integration solutions.
Key Responsibilities:
- Design, develop, and maintain scalable ETL/ELT pipelines for extracting, transforming, and loading data from multiple source systems.
- Build robust data ingestion and integration frameworks to process structured and unstructured data.
- Develop and optimize complex SQL queries, stored procedures, and data transformation logic.
- Design and manage automated data workflows using Apache Airflow.
- Implement batch and incremental data processing solutions to handle large volumes of enterprise data.
- Develop and maintain data models, data warehouses, and data processing frameworks.
- Monitor pipeline execution, troubleshoot failures, and optimize performance and resource utilization.
- Implement data validation, reconciliation, and quality checks to ensure accuracy and consistency.
- Collaborate with data architects, analysts, business stakeholders, and engineering teams to understand data requirements.
- Establish best practices for data pipeline development, code quality, documentation, and deployment.
- Support production data pipelines, resolve technical issues, and perform root cause analysis.
- Provide technical guidance and mentorship to junior data engineers.
Required Skills & Qualifications:
- 10 - 12 years of experience in Data Engineering, ETL Development, or Data Integration.
- Strong hands-on experience designing and developing enterprise-scale ETL/ELT pipelines.
- Advanced proficiency in SQL, including complex queries, joins, stored procedures, and query optimization.
- Strong experience with Apache Airflow for workflow orchestration, scheduling, and pipeline monitoring.
- Experience building data ingestion, transformation, and processing frameworks.
- Strong understanding of data warehousing concepts, dimensional modelling, and database architecture.
- Experience handling large datasets and complex data transformations.
- Knowledge of batch processing, incremental data loading, and data integration patterns.
- Experience with data quality, validation, reconciliation, and pipeline monitoring.
- Familiarity with version control systems such as Git and software development best practices.
- Strong analytical, troubleshooting, and problem-solving abilities.
Good to Have:
- Programming experience in Python or PySpark.
- Exposure to cloud-based data platforms such as AWS, Azure, or GCP.
- Familiarity with Snowflake, Databricks, Redshift, or similar data warehouse platforms.
- Experience with DBT or other data transformation frameworks.
- Knowledge of big data technologies such as Apache Spark and Hadoop.
- Experience implementing CI/CD practices for data engineering workflows.
Preferred Candidate Profile:
- Strong technical ownership of end-to-end data engineering solutions.
- Ability to work with cross-functional teams and translate business requirements into technical solutions.
- Experience reviewing code, defining engineering standards, and mentoring team members.
- Strong communication and stakeholder coordination skills.
Skills
Data Engineering, ETL, SQL, Apache Airflow, Data Warehousing, Python, PySpark, Databricks, Snowflake DB, Data Modeling