Data Engineer - Python/SQL/ETL
First seen by Alion on Aug 19, 2026.
Role : Data Engineer (3-5 Years)
About the role :
These pipelines are critical for powering product analytics, AI model evaluation, safety and reliability systems, and business decision-making across our agentic AI platform.
This role offers the opportunity to work closely with Product, Data Science, Infrastructure, Marketing, Finance and AI/Research teams, contributing to how our AI systems are trained, evaluated, and improved. As Bharat AI continues to grow rapidly, data-driven insights are central to our platform, and your work will have direct and visible impact.
In this role, you will :
- Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse.
- Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
- Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions.
- Implement robust and fault-tolerant systems for data ingestion and processing.
- Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.
- Ensure the security, integrity, and compliance of data according to industry and company standards.
You might thrive in this role if you :
- Have 3+ years of experience as a data engineer.
- Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
- Experience with distributed processing technologies and frameworks, such as Hadoop, Flink and distributed storage systems (e.g., HDFS).
- Expertise with any of ETL schedulers such as Airflow.
- Solid understanding of Spark and ability to write, debug and optimize Spark code.
Bonus to have :
- Hands-on experience working with Databricks in production environments.
- Familiarity with the GCP data stack, such as Pub/Sub, Dataflow, BigQuery, or GCS.
Skills
Data Engineering, Python, Data Modeling, SQL, ETL, Data Pipeline, Big Data, Hadoop, Scala, Spark, Azure Databricks