Data Architect

Responsibilities

Design and delivery of the following:

• Complex ETL/ELT processes, large-scale batch and real-time stream processing solutions, and optimizing data and schemas
• Data Lakes using native cloud tools or leveraging 3rd party platforms (for example Snowflake or Databricks)
• AI-based solutions for NLP, speech and video recognition, anomaly and fraud detection, chatbots, etc.
• End-to-end data solutions from ingestion pipelines, cataloging, analysis, and sharing insights (for example reports, dashboards, ML forecasts/predictions, etc.)
• Migrations and transformations of data services such as relational databases, NoSQL databases, and Data Warehouses (heterogeneous and homogeneous)
• Designing, building, training, and optimizing AI/ML solutions
• Designing and integrating MLOps solutions to support model lifecycle automation

Qualification

• s
  3+ years of experience in public cloud environments (AWS preferred
• ).3 + years of developing code using Python, Java, or Scala languag
• esExperience building complex data engineering pipelines and ETL/ELT tas
• ksExperience with relational databases (for example Oracle, SQL Server, MySQL, Postgres, MariaDB) or managed cloud RDBMS services (such as Amazon Auror
• a)Experience with NoSQL databases such as MongoDB, Cassandra, CouchDB, ElasticSearch, Neo4j, DynamoDB, BigTable, et
• c.Experience building batch processing and real-time processing system
• s.Experience building Data Warehouses and Data Lak
• esExperience with 3+ of the followin
• g:Building real-time streaming solutions leveraging technologies such as: Kafka, Kinesis, Pub/Sub messaging, event buses, or Spark Streami
• ngDesigning and implementing analytics and BI solutions such as MicroStrategy, Tibco, Qlikview, or Table
• auBuilding AI/ML solutions, including operations such as ongoing training, optimizations, and model deployment