onsite

Data Architect / Data Scientist

As a Data Architect / Data Scientist, you will design and build scalable, secure, and high-performance data platforms, supporting advanced analytics, AI/ML initiatives, and real-time data processing. You will work closely with engineering teams and business stakeholders to create modern data ecosystems and define data governance standards.

About the role

Your Role

As a Data Architect / Data Scientist, you will be responsible for designing scalable, secure, and high-performance data platforms. You will work closely with engineering teams and business stakeholders to build modern data ecosystems that support analytics, AI/ML initiatives, and real-time data processing.

In this role, you will:

Design end-to-end data architectures across cloud and hybrid environments.
Build scalable data pipelines, data lakes, and modern data platforms.
Architect ingestion frameworks for IoT and sensor data, particularly for Digital Twin platforms.
Develop and optimize data models for structured, semi-structured, and unstructured data.
Implement real-time data ingestion using streaming and messaging frameworks.
Collaborate with cross-functional teams to align data strategies with business goals.
Define and enforce data governance, security, quality, and compliance standards.
Guide engineering teams on best practices for data architecture and technology selection.
Create architectural documentation including data flow diagrams and design artifacts.
Evaluate emerging technologies and optimize systems for performance, scalability, and cost.

Your Profile

6–9 years of progressive experience in data engineering and data architecture.
Strong experience designing scalable and secure data platforms.
Hands-on expertise with AWS data services and modern data platforms.
Strong analytical, problem-solving, and communication skills.
Experience working with cross-functional teams in agile environments.
Bachelor’s or Master’s degree in Engineering, Computer Science, or a related field (Data Science / Information Systems / Data Architecture specialization preferred).

Core Skills & Expertise

Cloud Expertise: AWS (Kinesis, EMR, Glue, RDS, Athena, Redshift, Lambda, S3)
Data Platform Design: Snowflake, scalable data pipelines, data lake architectures
Digital Twin Integration: IoT data ingestion, sensor data modeling, real-time systems
Data Modeling: Conceptual, logical, and physical modeling across data types
Programming & Querying: Python, PySpark, Advanced SQL
Big Data Ecosystem: Hadoop, Spark, Kafka
Database Management: SQL Server, MySQL, PostgreSQL, Oracle, MongoDB, Cassandra
Data Governance & Quality: Lineage, metadata management, quality frameworks
DevOps & CI/CD: Deployment automation and pipeline management for data platforms
Streaming & Queuing: Real-time ingestion architectures
Time Series Data: Design for ingestion, storage, and analysis of time-based data

About the role

Your Role

In this role, you will:

Design end-to-end data architectures across cloud and hybrid environments.
Build scalable data pipelines, data lakes, and modern data platforms.
Architect ingestion frameworks for IoT and sensor data, particularly for Digital Twin platforms.
Develop and optimize data models for structured, semi-structured, and unstructured data.
Implement real-time data ingestion using streaming and messaging frameworks.
Collaborate with cross-functional teams to align data strategies with business goals.
Define and enforce data governance, security, quality, and compliance standards.
Guide engineering teams on best practices for data architecture and technology selection.
Create architectural documentation including data flow diagrams and design artifacts.
Evaluate emerging technologies and optimize systems for performance, scalability, and cost.

Your Profile

6–9 years of progressive experience in data engineering and data architecture.
Strong experience designing scalable and secure data platforms.
Hands-on expertise with AWS data services and modern data platforms.
Strong analytical, problem-solving, and communication skills.
Experience working with cross-functional teams in agile environments.
Bachelor’s or Master’s degree in Engineering, Computer Science, or a related field (Data Science / Information Systems / Data Architecture specialization preferred).

Core Skills & Expertise

Cloud Expertise: AWS (Kinesis, EMR, Glue, RDS, Athena, Redshift, Lambda, S3)
Data Platform Design: Snowflake, scalable data pipelines, data lake architectures
Digital Twin Integration: IoT data ingestion, sensor data modeling, real-time systems
Data Modeling: Conceptual, logical, and physical modeling across data types
Programming & Querying: Python, PySpark, Advanced SQL
Big Data Ecosystem: Hadoop, Spark, Kafka
Database Management: SQL Server, MySQL, PostgreSQL, Oracle, MongoDB, Cassandra
Data Governance & Quality: Lineage, metadata management, quality frameworks
DevOps & CI/CD: Deployment automation and pipeline management for data platforms
Streaming & Queuing: Real-time ingestion architectures
Time Series Data: Design for ingestion, storage, and analysis of time-based data