Big Data Solution Architect - Pune

Hi,

Wishes from GSN!!! Pleasure connecting with you!!!

We been into Corporate Search Services for Identifying & Bringing in Stellar Talented Professionals for our reputed IT / Non-IT clients in India. We have been successfully providing results to various potential needs of our clients for the last 20 years.

At present, GSN is one of our leading MNC client.

PFB the details for your better understanding:

• WORK LOCATION: PUNE

• Job Role:

  Big Data Solution Architect

• EXPERIENCE:

  10 Yrs - 20 Yrs

• CTC Range:

  25 LPA -35 LPA

• Work Type: Hybrid

Required Skills & Experience:

• 10+ years of progressive experience in software development, data engineering, and solution architecture roles, with a strong focus on large-scale distributed systems.

• Expertise in Big Data Technologies

  :

• Apache Spark

  : Deep expertise in Spark architecture, Spark SQL, Spark Streaming, performance tuning, and optimization techniques. Experience with data processing paradigms (batch and real-time).

• Hadoop Ecosystem

  : Strong understanding of HDFS, YARN, Hive, and other related Hadoop components.

• Real-time Data Streaming:

• Apache Kafka: Expert-level knowledge of Kafka architecture, topics, partitions, producers, consumers, Kafka Streams, KSQL, and best practices for high-throughput, low-latency data pipelines.

• NoSQL Databases:

• Couchbase: In-depth experience with Couchbase (or similar document/key-value NoSQL databases like MongoDB, Cassandra), including data modeling, indexing, querying (N1QL), replication, scaling, and operational best practices.
• API Design & Development: Extensive experience in designing and implementing robust, scalable, and secure APIs (RESTful, GraphQL) for data access and integration.

• Programming & Code Review:

• Hands-on coding proficiency in at least one relevant language (Python, Scala, Java) with a preference for Python and/or Scala for data engineering tasks.
• Proven experience in leading and performing code reviews, ensuring code quality, performance, and adherence to architectural guidelines.

• Cloud Platforms

  : Extensive experience designing and implementing solutions on at least one major cloud platform (AWS, Azure, GCP), leveraging their Big Data, streaming, and compute services.

• Database Fundamentals:

  Solid understanding of relational database concepts, SQL, and data warehousing principles.

• System Design & Architecture Patterns

  : Deep knowledge of various architectural patterns (e.g., Microservices, Event-Driven Architecture, Lambda/Kappa Architecture, Data Mesh) and their application in data solutions.

DevOps & CI/CD: Familiarity with DevOps principles, CI/CD pipelines, infrastructure as code (IaC), and automated deployment strategies for data platforms.

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