- Location
- Noida, Uttar Pradesh, India
- Job type
- Full-time
Required skills
- Python
- Airflow
- AWS
- Apache
- Apache Airflow
- Azure
- BigQuery
- CI
- Databricks
- Elasticsearch
- end-to-end
- ETL
- GCP
- Git
- Kafka
- NoSQL
- Oracle
- React
- SQL
- TypeScript
About the role
Website:
Job details:
Key Responsibilities
- Build and optimize end-to-end ETL/ELT pipelines for structured and semi-structured data using Python, PySpark and Databricks.
- Automate complex workflows using Apache Airflow and manage cloud-native services (AWS Glue/Lake Formation or Azure Data Factory).
- Implement real-time ingestion layers using Kafka, AWS MSK, or Kinesis to ensure low-latency data availability.
- Maintain and query relational databases (SQL Server, Oracle) while ensuring high data integrity and performance.
- Manage code versions via Git and contribute to CI/CD pipelines for automated cloud resource deployment.
Technical Requirements
- 4+ years of professional experience in a Data Engineering role.
- Strong proficiency in Python and SQL.
- Hands-on experience with Spark/Databricks for large-scale processing.
- Proven experience in either AWS (Glue, Kinesis, Lake Formation) or Azure (ADF, Event Hubs), GCP (BigQuery).
- Ability to translate technical pipeline architecture into clear business value for stakeholders.
Good to Have
- Experience with Geospatial data formats and algorithms.
- Experience with AI/ML.
- Experience with Trino SQL.
- Familiarity with NoSQL environments (ElasticSearch, Graph Databases).
- Web fundamentals: Basic knowledge of React/TypeScript for data-heavy applications.
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