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.