Data Engineer
ADA Global9 days ago
Bengaluru, IndiaEntry Level
Responsibilities
- Assist with developing and maintaining data connectors and ingestion pipelines for APIs, databases, files, and SaaS tools.
- Extract, transform, and load data into the data platform using ETL/ELT processes.
- Understand source schemas, APIs, and data formats including JSON, CSV, and relational tables.
- Implement data transformations, validations, and quality checks.
- Write clean, maintainable, and testable code under senior engineer guidance.
- Perform unit and basic integration testing of data pipelines and connectors.
- Debug data issues, pipeline failures, and synchronization issues.
- Document connectors, pipelines, and operational runbooks.
- Use Git and CI/CD pipelines for versioning and deployments.
- Follow coding standards, engineering practices, and data governance guidelines while collaborating with senior data engineers, QA, and product teams.
Requirements
- Bachelor’s degree in computer science, IT, engineering, or a related field.
- 0–1 years of experience.
- Basic to good knowledge of Python and SQL.
- Basic understanding of ETL, data pipelines, and data warehousing.
- Familiarity with REST APIs and JSON/CSV data.
- Basic understanding of databases such as MySQL or Postgres.
- Awareness of Git and version control systems.
- Willingness to learn debugging, monitoring, and production support for data pipelines.
- Good problem-solving, attention to detail, communication skills, and eagerness to learn.
- Preferred but not mandatory: exposure to PySpark, Spark, Databricks, or EMR; basic cloud knowledge; CI/CD knowledge; internship or academic projects in data engineering, backend, or ETL; and basic data modeling or data warehousing knowledge.
Benefits
- The role is based onsite in Bengaluru.
Tech Stack
Categories
Data Engineering
About ADA Global
ADA Global builds data and AI platforms and services that help enterprises manage identity and authentication, personalization, commerce, and analytics across channels. Operating in 14 markets, it serves more than 1,500 brands in CPG, retail, telecommunications, financial services, and healthcare. Its business combines software and managed services, including cloud-native deployment, data engineering, and applied machine learning to improve customer experience and growth outcomes.