Senior Data & AI Engineer

Key Capabilities

Data Engineering

Cloud-native data architectures (AWS / Azure / GCP), ETL/ELT pipelines, data modeling, API and database integration, workflow orchestration (Airflow), batch and real-time processing.

AI & Machine Learning

Model development and deployment, feature engineering, MLOps fundamentals, predictive analytics, AI integration within data ecosystems, cloud AI services and frameworks.

Generative AI

LLM integration, prompt engineering, RAG architectures, embeddings, vector databases, AI-driven automation, conversational AI workflows.

Cloud & Tools

AWS (S3, Glue, Lambda, Redshift, Athena, EMR, Kinesis)
Azure (Data Factory, Synapse, Databricks, Azure AI Services)
GCP (BigQuery, Dataflow, Pub/Sub, Vertex AI)
Spark, Kafka, Snowflake, Databricks, Airflow.

Programming & DevOps

Python, SQL, Scala/Java, Docker, Kubernetes, CI/CD pipelines, Git/GitHub.

Experience

5+ years of experience in Data Engineering with exposure to AI/ML and cloud-based analytics projects.

Projects

You will be part of a collaborative and innovative team focused on delivering high-quality solutions through data analysis, data optimization, and emerging technologies. The team works on projects designed to improve operational efficiency, support strategic decision-making, and create scalable solutions for different business needs.

Profile Summary

Senior engineer with strong experience building modern data platforms across AWS, Microsoft Azure, or Google Cloud Platform (GCP), while integrating AI capabilities into real business processes. Experienced in developing scalable data pipelines, real-time processing solutions, analytics environments, and cloud-native architectures that support advanced analytics, machine learning, and generative AI initiatives.

Focused on practical, scalable, and business-oriented solutions with emphasis on data quality, automation, and operational efficiency.

Certifications (Optional)

• AWS Data Analytics / Solutions Architect
• Azure Data Engineer Associate
• Google Professional Data Engineer
• AWS / Azure / GCP AI Certifications
• Machine Learning or Generative AI certifications

Soft Skills

• Clear communication with technical and business teams.
• Strong analytical and problem-solving mindset.
• Client-oriented and results-driven approach.
• Comfortable working with distributed and multicultural teams.
• Continuous learning mindset in cloud and AI technologies.