Senior Software Engineer, Data Platform
New
Full-time remote opportunity for candidates based in India.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years of experience
- Required Skills
- PythonSQLSnowflakeAirflowApache KafkaData engineeringSparkDistributed Systems
Requirements
- 7+ years of experience in software engineering or data engineering roles within production-scale, high-traffic environments.
- Proven experience building and maintaining batch and real-time data pipelines.
- Strong understanding of distributed systems concepts, including scalability, reliability, fault tolerance, and performance optimization.
- Strong proficiency in Python and SQL.
- Hands-on experience with streaming technologies such as Kafka or similar platforms.
- Experience with Spark Structured Streaming and open table formats such as Apache Iceberg, Delta Lake, or Hudi.
- Experience working with cloud data warehouses, with Snowflake experience strongly preferred.
- Familiarity with workflow orchestration tools such as Airflow or similar solutions.
- Ability to build and use AI agents for engineering and operational tasks.
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.
- Experience with CDC patterns, DBT, and big data technologies like Spark, Flink, or Pinot is a plus.
Responsibilities
- Design, build, and operate scalable data ingestion and transformation pipelines supporting both real-time and batch workloads.
- Develop reliable solutions for onboarding new data sources, managing integrations, and evolving existing data platform capabilities.
- Contribute to the architecture and development of core data platform components, including storage, compute, and pipeline infrastructure.
- Build automation tools for monitoring, alerting, data quality measurement, and self-service capabilities.
- Diagnose and resolve production issues by identifying root causes and implementing long-term systemic improvements.
- Participate in on-call rotations by managing incidents, driving resolution, and contributing to post-incident improvements.
- Develop and leverage AI-powered agents to automate engineering and operational workflows.
- Collaborate with engineering and analytics teams to deliver reliable, scalable, and high-quality data solutions.
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