Overview
Data Engineering MTS role contributing to the development and maintenance of automated data pipelines for analytics.
What you'll do
- Develop and maintain automated data pipelines for ingesting, transforming, and delivering analytics datasets.
- Work with senior engineers to implement data transformations and models for reporting and analysis.
- Collaborate with data analysts, data scientists, and product teams to understand data requirements and support data flow.
- Assist with data modeling and schema implementation for analytics-friendly structures.
- Support data quality checks, validation, and monitoring to identify and resolve inconsistencies.
- Participate in ad-hoc data analysis and queries for business questions.
- Adopt data engineering best practices including version control, testing, and CI/CD workflows.
What you'll need
- 3+ years of experience building, implementing, and maintaining data warehousing and analytics solutions.
- Hands-on distributed data processing experience with frameworks such as Spark, Hive, or Iceberg.
- Proficiency in SQL, including complex queries and performance optimization for analytical workloads.
- Working knowledge of Python, Java, or Scala for data transformation and pipeline development.
- Experience building and maintaining data pipelines using Spark (SparkSQL) and orchestration tools such as Airflow (or equivalent).
- Exposure to MPP analytical databases (e.g., Snowflake, Redshift) and query performance considerations.
Nice to have
- Exposure to building or extending AI agents and LLM-powered applications.
- Experience integrating data from multiple sources using APIs or standard ingestion mechanisms.
- Familiarity with cloud platforms, preferably AWS.
- Exposure to AI-assisted development tools to improve developer productivity.
Details
- Location: Bangalore, India.
Read the full description and apply on the company’s own careers page.
