Analytics Architect - Analytics & IT Firm

10 - 12 Years

Bangalore

Posted 3 years ago

#Analytics #Technical Architect #Data Analytics #Data Management #Python #Big Data #Data Warehousing #Machine Learning #NLP #SQL

Analytics Architect - Analytics & IT

Responsibilities :

- Lead cross-team of Application Engineers, Data Scientists, Computational Linguists to deliver high quality features against tight timeline while promoting collaborative environment

- Educate the team on design principles and architectural choices made

- Provide solid software/component level designs supporting technical requirements

- Own strategy and technical roadmap of product components and services

Skills Required :

Key Skills :

- Python, Flask, Spark, Airflow, Hadoop, Web Services, MongoDB, Redis

- 10+ years of IT experience with at least 3+ years in architect role

- Strong coding skills with 5+ years of experience in modern languages such as Python, Go

- Well versed with current trends and design patterns for developing systems and services which work seamlessly in private, public and hybrid clouds

- Proven experience in building B2B products preferably Analytics products which are robust, high performant and intelligent

- Have experience in Distributed Systems, High-Performance computing, UI Engineering, Information Visualisation, Machine Learning etc.

- Strong problem-solving skills, algorithmic thinking and a strong foundation in how systems work

- Deep understanding on microservices design patterns, service registry and discovery, externalization of configurations

Must have worked on the following skills :

- Big data - Spark, Databricks, Hadoop, Kafka, Hive, Presto, HDFS etc.

- Data pipeline - Airflow, Azkaban

- API gateway frameworks - Kong, MuleSoft, Apigee etc

- NoSQL stores - MongoDB, Elasticsearch, Cassandra, Redis or equivalent

- RDBMS - Oracle, PostgreSQL, MySQL

- Data warehouse - Redshift, Azure SQL DW, Snowflake, Google Big Query

- Security - OAuth2, OpenID, SAML, Kerberos, Apache Ranger

- DevOps - Docker, Kubernetes

- Knowledge in Machine Learning, Deep Learning, NLP tools and frameworks

- Knowledge in python libraries like Pandas, Numpy, Scikit, TensorFlow, Keras, NLTK, Spacy