Position Overview

We are seeking a hands-on Data Engineering Architect to design and build scalable data pipelines, implement cutting-edge Generative AI features, and architect robust data solutions. This role requires a technical leader who can translate business requirements into sophisticated data architectures while actively contributing to code development and system implementation.

Roles & Responsibilities

Architecture & Design

• Design and implement end-to-end data pipelines supporting batch and real-time processing
• Architect scalable data solutions using modern cloud-native patterns and microservices
• Develop comprehensive data strategies integrating traditional databases with cloud data platforms
• Lead technical decision-making for data platform evolution and technology stack optimization

Generative AI & Machine Learning

• Build and deploy Generative AI features using AWS Bedrock foundation models
• Implement RAG (Retrieval-Augmented Generation) architectures with vector databases
• Design ML inference pipelines with proper monitoring, scaling, and cost optimization
• Integrate AI/ML capabilities into existing data workflows and applications

Hands-On Development

• Write production-quality code in Java and Python for data processing and API development
• Develop data transformation logic, ETL/ELT processes, and data quality frameworks
• Implement event-driven architectures using messaging systems and stream processing
• Build and maintain data integration connectors and APIs

Data Platform Management

• Optimize data storage strategies across relational databases and cloud data warehouses
• Implement data governance, security, and compliance frameworks
• Monitor and optimize system performance, reliability, and cost efficiency
• Establish CI/CD pipelines for data infrastructure and applications

Required Technical Skills

Programming Languages

• Java: 5+ years of experience with Spring Framework, microservices, and enterprise applications
• Python: Strong proficiency in data processing libraries (Pandas, NumPy), API frameworks (FastAPI, Flask)

Cloud & AWS Services

• AWS Bedrock: Experience with foundation models, model fine-tuning, and inference endpoints
• Core AWS Services: S3, EC2, Lambda, IAM, VPC, CloudFormation/CDK
• Messaging & Streaming: SQS, SNS, Kinesis, and Apache Kafka
• Search & Analytics: OpenSearch/Elasticsearch for full-text search and analytics

Database Technologies

• Snowflake: Data warehouse design, performance optimization, and integration patterns
• MySQL: Advanced SQL, query optimization, replication, and high-availability configurations
• SQL Server: T-SQL, stored procedures, SSIS/ETL development, and performance tuning

Data Engineering Tools

• Workflow orchestration (Apache Airflow, AWS Step Functions, or similar)
• Data processing frameworks (DBT, Apache Spark, Dask, or similar)
• Container technologies (Docker, Kubernetes, ECS/EKS)
• Version control and CI/CD (Git, Jenkins, GitLab CI, BitBucket, etc. )

Education / Qualifications

Experience & Background

• 7+ years in data engineering, software architecture, or related technical roles
• 3+ years of hands-on experience with AWS services in production environments
• Experience with large-scale data processing (TB/PB scale datasets)
• Background in building real-time analytics or ML-powered applications

Domain Knowledge

• Experience with building reporting solutions that provides insights to the end users.
• Experience working with LLMs and building ML features for the users.
• Understanding of Quality Management Systems, data privacy regulations (GDPR, CCPA) and security best practices
• Experience with data mesh, data fabric, or modern data architecture patterns
• Knowledge of DevOps practices and infrastructure-as-code methodologies
• Familiarity with monitoring and observability tools (CloudWatch, Datadog, ELK stack)

Soft Skills

• Strong analytical and problem-solving abilities with attention to detail
• Excellent communication skills with ability to explain complex technical concepts
• Experience mentoring junior developers and leading technical initiatives
• Collaborative mindset with cross-functional teams (product, data science, engineering)
• Proven ability to convert POCs into production-grade solutions.

Education Requirements

• Bachelor's degree in Computer Science, Engineering, or related technical field
• Master's degree preferred but not required with sufficient experience
• Relevant AWS certifications (Solutions Architect, Data Engineer) are a plus

What You'll Build

• Scalable data pipelines processing millions of events daily
• GenAI-powered features enhancing user experiences and business insights
• Real-time analytics systems supporting critical business decisions
• Robust data infrastructure supporting multiple business units and use cases

Growth Opportunities

• Lead architecture decisions for next-generation data platform
• Drive adoption of emerging AI/ML technologies and best practices
• Mentor and grow a team of talented data engineers
• Shape data strategy and technical roadmap for the organization

About Hexagon

Hexagon is a global leader in digital reality solutions, combining sensor, software and autonomous technologies. We are putting data to work to boost efficiency, productivity, quality and safety across industrial, manufacturing, infrastructure, public sector, and mobility applications. 
 
Hexagon’s Asset Lifecycle Intelligence division helps clients design, construct, and operate more profitable, safe, and sustainable industrial facilities. We empower customers to unlock data, accelerate industrial project modernization and digital maturity, increase productivity, and move the sustainability needle. 
 
Our technologies help produce actionable insights that enable better decision-making and intelligence across the asset lifecycle of industrial projects, leading to improvements in safety, quality, efficiency, and productivity, which contribute to Economic and Environmental Sustainability. 
 
Hexagon (Nasdaq Stockholm: HEXA B) has approximately 25,000 employees in 50 countries and net sales of approximately 5.4bn EUR. Learn more at hexagon.com and follow us @HexagonAB. 

Why work for Hexagon?

At Hexagon, if you can see it, you can do it. Hexagon’s Asset Lifecyle Intelligence division puts their trust in you so that you can bring your ideas to life. We have emerged as one of the most engaged and enabled workplaces*. We are committed to creating an environment that is truly supportive by providing the resources you need to fully support your ambitions, no matter who you are or where you are in the world. 
 
* In the recently concluded workplace effectiveness survey by Korn Ferry, a global HR advisory firm, Hexagon, Asset Lifecycle Intelligence division has emerged as one of the most Engaged and Enabled workplaces, when compared to similar organizations that Korn Ferry partners with. 

Everyone is welcome

At Hexagon, we believe that diverse and inclusive teams are critical to the success of our people and our business. Everyone is welcome—as an inclusive workplace, we do not discriminate. In fact, we embrace differences and are fully committed to creating equal opportunities, an inclusive environment, and fairness for all. 
 
Respect is the cornerstone of how we operate, so speak up and be yourself. You are valued here.