Data Solution Architect

We are looking for Solution Architects any level for data-driven projects. Together we design and drive lots of solutions which generate value from data, taking advantage of scalable platforms, cutting-edge technologies, and machine learning algorithms.

Set of used technologies is very wide, so any technology background of the Solution Architect is acceptable. We provide a solid architecture framework, educational programs, and strong SA community to support you in a deep dive to data domain.

SOME ARCHITECTURAL AREAS WE ARE FOCUSING ON

• Data Processing Architecture
• Streaming Architecture
• Data Platform Operations
• Metadata Management Architecture
• Cloud Data Services Architecture
• ML and MLOps Architecture
• Data Warehouse Architecture
• Data Management
• Business Intelligence Solutions
• Data Integration Architecture
• Data Security Architecture

SOME EXAMPLES FROM TOOL SET/TECHNOLOGY STACK WE ARE USING

• Clouds: AWS, Azure, GCP
• Distributed data processing & ETL Frameworks: Apache Spark (and related cloud specific technologies such as AWS EMR, GCP DataProc, Azure HD Insight), GCP DataFlow, AWS Glue, Databricks
• Distributed Environments: Kubernetes, Docker, AWS ECS, Google Kubernetes Engine, Azure Kubernetes Services
• Analytical Data Warehousing: Snowflake, AWS Redshift, Azure Synapse, GCP BigQuery
• Relational Databases: PostgreSQL, AWS SQL DB, GCP Cloud SQL
• Lightweight/Serverless Compute: AWS Lambda Functions, GCP Cloud Functions, Azure Functions
• No-SQL/Specialized Databases: Cassandra, MongoDB, Azure Cosmos DB, GCP BigTable, Redis (including cloud analogs)
• Data Catalogs & Metadata Management: Collibra, Alation, Informatica,Azure Purview, Google Dataplex
• Integration & flow management: AWS Step Functions, Airflow/ GCP Cloud Composer, Azure Data Factory, Kafka Connect
• Data Streaming: Kafka, AWS Kinesis, GCP Pub/Sub, Azure Event Hub
• Object storages: S3, ADLS, GCS, HDFS, Minio
• Search platforms: Solr, ElasticSearch
• ML: MLflow, Kubeflow, AWS Sagemaker, Azure ML, GCP AI Platform
• Data Visualization: Power BI, Tableau, QlikView, Spotfire, Jupyter
• Platform Operations: IaaC (Terraform, AWS CloudFormation, Azure DevOps etc.), IaM (Azure AD, AWS Cognito, etc.), monitoring (Prometheus, Splunk, Azure Monitor, etc.), CI/CD (Jenkins, GCP Cloud Build, etc.), Cloud cost managment, secuity & networking tools
• Programming Languages: Java, Scala, Python