Sr. Data Engineer - Data Analytics
New
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- AWSPythonSQLApache AirflowTypeScriptApache KafkaGoSparkScala
Requirements
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related technical field.
- 7+ years of experience in data engineering or backend/data platform development roles.
- Strong hands-on experience with real-time, event-driven architectures and streaming systems.
- Proficiency in at least one modern programming language such as Python, Scala, Go, or TypeScript.
- Experience building and maintaining complex data processing pipelines in production environments.
- Strong knowledge of data modeling techniques (e.g., star schema, dimensional modeling).
- Experience with query optimization and performance tuning for large-scale data systems.
- Familiarity with AWS data ecosystem and distributed data processing frameworks (e.g., Spark, Flink, EMR).
- Experience with Airflow, Kafka (preferred), and modern CI/CD workflows (GitLab).
- Strong problem-solving mindset with ability to work independently in a global, remote team setup.
Responsibilities
- Design and implement scalable, low-latency real-time data streaming architectures and end-to-end data pipelines for high-volume systems.
- Develop clean, maintainable, and efficient code using technologies such as Go, Python, TypeScript/Node.js, Scala, and SQL.
- Build and optimize complex data processing workflows handling structured and unstructured data sources.
- Contribute to architecture decisions and delivery of key platform modules supporting real-time analytics and data-driven products.
- Work with AWS-based data services including Kinesis, Lambda, SQS, Redshift, Glue, Athena, and related big data technologies.
- Improve system performance, reliability, and observability through continuous optimization and production monitoring.
- Participate in CI/CD-based deployment processes and ensure smooth production releases and system stability.
- Mentor team members by sharing knowledge, providing feedback, and promoting engineering best practices.
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