Data Engineer Streaming & APIs

4 - 9 years

10 - 15 Lacs

Posted:2 hours ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

Purpose

Design, develop, and optimize scalable data solutions for real-time streaming and batch processing, with a focus on data enrichment, API exposure, and business intelligence.

Key Responsibilities

  • Architect scalable ETL/ELT data pipelines for streaming logs (Spark, Kafka) and batch processing.
  • Develop high-performance APIs using FastAPI to serve enriched data (e.g., IP geolocation, user mapping) to internal applications.
  • Integrate external data sources and optimize queries for concurrent access.
  • Manage the data lifecycle including compaction, cold storage migration (S3), and cost optimization.
  • Lead stress testing (load, concurrency) and document technical designs to support scalability (10x100x growth).

Technical Requirements

Core Skills:

  • Minimum 4 years of experience in Python for Big Data (Spark/Hadoop); experience with ELK/Elastic Stack is a plus.
  • At least 2 years of experience in API development (FastAPI/Flask), streaming technologies (Kafka/Spark Streaming), and containerization (Kubernetes).
  • Strong proficiency in SQL, pandas, numpy, and cloud storage (S3).

Design Skills:

  • Expertise in system architecture, UML, and API integration.

Flexibility:

  • Candidates with experience in ELK/Elastic, AWS Kinesis, or similar tools are encouraged to apply if they demonstrate rapid learning ability.

Soft Skills

  • Strong analytical problem-solving skills for performance and scalability challenges.
  • Clear and effective communication for documenting architectures and collaborating across teams.
  • Results-driven mindset with a focus on SLAs and KPIs such as latency, throughput, and data accuracy.

Candidate Profile:

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