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Python Spark-1386614
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| Ref No.: |
25-00877 |
| Location: |
Mumbai, Maharashtra
|
| Position Type: | Contract |
| Experience Level: | 3 Years |
Key Responsibilities
- Design, develop, and optimize scalable data pipelines using Python and Apache Spark.
- Build high-performance data workflows with pushdown optimization, streaming, replication, partitioning, and clustering techniques.
- Evaluate and integrate modern data platforms and tools into our enterprise architecture.
- Engineer and manage feature pipelines to support real-time fraud detection systems.
- Design data models and processing strategies that align with distributed system principles, ensuring scalability, consistency, and performance across large-scale environments.
- Develop solutions that are production-ready, maintainable, and built with observability and operational excellence in mind.
- Apply clean code practices, SOLID principles, and architecture patterns to deliver robust and extensible systems.
- Participate in code reviews, testing, and deployment activities.
- Contribute to architectural decisions and continuous improvement initiatives.
Required Skills
- 3+ years of professional experience in Python development with a strong focus on data engineering.
- Hands-on expertise with Apache Spark and Big Data processing.
- Strong SQL skills and experience with both relational and distributed data systems.
- Solid understanding of software engineering principles, clean code, and design patterns.
- Experience in system design and architecture for scalable, data-intensive applications.
- Ability to evaluate new technologies and recommend solutions aligned with enterprise needs.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration abilities.
Beneficial Skills (Nice to have)
- Exposure to cloud platforms such as Snowflake, Databricks, or similar.
- Familiarity with Kafka, Redis, Airflow, Jenkins, and Git.
- Understanding of observability practices and tools like Open Telemetry, Grafana, Loki, or Tempo, with a mindset for embedding observability into system design.
- Awareness of Kubernetes, Helm, GitOps, and containerization concepts.
- Background in real-time systems, or financial services domains.
- Good sense of humor
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