Solution Architect/Big Data Architect - IT

As a Big Data Architect, you will shape the data landscape for leading Fortune 500 organisations. You will be in a senior level customer facing role that requires expertise in a variety of big data solution architecture. The role requires deep hands-on expertise in data engineering, along with knowledge of a variety of big data ecosystem technologies. You will guide strategic customers as they implement transformational projects, including end-to-end design, build and deployment of industry-leading big data and AI applications. Above all, you should be passionate about working with huge data sets and someone who loves to bring data-sets together to answer business questions and drive change.

- Work with huge data sets to design and implement scalable, reliable, high performance, fault tolerant platforms.

- A customer-centric, intellectually curious, bright, energetic person with the ability to drive and deliver successfully

- Ability to articulate ideas to both technical and non-technical stakeholders.

- Technology evaluation, architecture & design, estimation, implementation, testing and technical reviews of highly scalable platforms, solutions and technology building blocks to address customer's requirement.

- Lead the overall technical solution implementation as part of customer's project delivery team

- Mentor and groom project team members in the core technology areas, usage of SDLC tools and Agile

- Engage in external and internal forums to demonstrate thought leadership

- Knowledge in Artificial Intelligence and Machine Learning is a bonus.

Skills Required:

- 15+ years of overall work experience with at least 7 years working as a Big Data Architect. Strong hands-on work experience in architecting, designing and implementing data solutions including multiple below skills:

- Scalable databases or object stores: Cassandra, MongoDB, AWS DynamoDB, Hbase, Minio. Experience on in-memory databass like Gemfire or Timesten will be an advantage.

- Data integration: Both batch and streaming. Ingestion mechanism like Kinesis, Kafka, NiFi, AWS Glue, Stitch, Confluent

- Data warehousing: SnowFlake, Databricks , RedShift

- Programming Languages: Core Java, Spring, Spring boot, Python, Scala

- Caching: Redis, Hazelcast, Infinispan

- Distributed Data Processing: Hadoop Map Reduce, Parallel Processing, Stream Processing, Flume, Spark, PySpark, Flink

- DevOps: Docker, Kubernetes, Ansible, Chef

- Data Quality, Data Governance and Data Catalog: Apache Atlas, Ranger, Talend, DataLadder, Apache Griffin and Cloud Native Services

Other skills: DataOps, Machine Learning, Mathematical background & NLP