Data Engineer I
Circles (company site, opens in a new tab)1+ yrsOn-siteDirect career pageEst. 8–16 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and support scalable cloud-native data platforms and batch/streaming data pipelines to power analytics, reporting, and machine learning across multiple markets.
- Own end-to-end data engineering initiatives including solution design, testing, deployment, performance tuning, and production support to ensure reliability and high quality.
- Collaborate closely with product, analytics, platform engineering, and other cross-functional teams to deliver enterprise-scale data solutions aligned with strategic goals.
Minimum Requirements
- At least 1+ years of experience in Data Engineering or Big Data roles.
- Strong experience with ETL/ELT pipeline development using Python, Spark/PySpark, and SQL.
- Hands-on experience with modern data lakehouse technologies (e.g., Apache Iceberg, Hive, Trino, BigQuery, Redshift, ClickHouse, or Snowflake) and cloud object storage solutions such as Amazon S3.
- Experience deploying and managing data applications on Kubernetes and implementing CI/CD pipelines using GitLab CI/CD, or familiarity with related container orchestration and pipeline tools.
Ideal Candidate Profile
- Has practical experience building scalable, production-grade data platforms supporting multi-market, telecom or similar data environments.
- Comfortable working in fast-paced settings requiring independent problem-solving, root cause analysis, and continuous platform optimization.
- Demonstrates ability to manage cross-team collaboration with product, analytics, and engineering stakeholders to translate business requirements into technical implementations.