Senior Data Engineer
Actively Reviewing the ApplicationsAuxo AI
Bengaluru
Full-Time
4–8 years
Posted 5 days ago
•
Apply by June 11, 2026
Job Description
Description
We are seeking a seasoned Senior Data Engineer to join our team. In this role, you will design, build, and optimize the data architecture that powers our analytics and business intelligence. You will be responsible for creating robust ETL/ELT pipelines, ensuring data quality at scale, and leveraging cloud technologies to solve complex data challenges.
Core Responsibilities
We are seeking a seasoned Senior Data Engineer to join our team. In this role, you will design, build, and optimize the data architecture that powers our analytics and business intelligence. You will be responsible for creating robust ETL/ELT pipelines, ensuring data quality at scale, and leveraging cloud technologies to solve complex data challenges.
Core Responsibilities
- Pipeline Architecture : Design and implement highly scalable, end-to-end data pipelines using PySpark and Python to process large-scale structured and unstructured data.
- Data Modeling : Develop and maintain complex data models (Star Schema, Snowflake Schema, Data Vault) that support high-performance analytics.
- Cloud Strategy : Manage and optimize data environments in at least one major cloud platform (AWS, Azure, or Snowflake).
- Performance Tuning : Optimize heavy-duty SQL queries and Spark jobs to reduce processing time and minimize cloud infrastructure costs.
- Collaboration : Work closely with Data Scientists and Business Analysts to translate raw data into actionable insights and reliable data products.
- Mentorship : Provide technical leadership and conduct code reviews for junior engineers to ensure high coding standards and best practices.
- Experience : 5 to 10 years of hands-on experience in Data Engineering or a similar backend engineering role.
- Languages (Mandatory) : Expert-level proficiency in Python and SQL.
- Big Data : Deep experience with PySpark (Spark SQL, DataFrames) for distributed data processing.
- Cloud Platforms : Proven expertise in any one of the following :
- AWS :
- Glue
- EMR
- Redshift
- S3
- Lambda
- Azure :
- Data Factory
- Synapse
- Databricks
- ADLS
- Snowflake :
- Snowpipe
- Streams
- Tasks
- Snowpark
- Orchestration : Experience with workflow tools like Apache Airflow, Prefect, or Dagster.
- DevOps/CI/CD : Proficiency with Git, Jenkins/GitHub Actions, and automated deployment of data pipelines.
Required Skills
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