Hexagon - Data Engineering Architect

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