- Design and build scalable cloud-native data platforms from greenfield to production
- Design and implement near-real-time ingestion pipelines using event-driven patterns
- Define and enforce data platform standards including Data Lake and Lakehouse principles, medallion architecture, and data contracts
- Refactor, optimize, and modernize Spark and PySpark scripts for performance and maintainability
- Introduce best practices for code quality, testing, and CI/CD across data pipelines
- Drive adoption of AI tooling and agentic workflows within the Data Engineering team
- Ensure data quality, observability, scalability, and reliability across all platforms and pipelines
- Design and deliver self-service tooling and microservices that simplify platform usage
- Collaborate with cross-functional stakeholders including Product, Machine Learning, and Data Science teams
- Contribute to architecture decisions and technical R&D initiatives
- 5+ years of professional experience in Data Engineering
- Strong Python and SQL development skills
- Hands-on experience with Apache Spark and PySpark including query optimization and performance tuning
- Experience working with Databricks or Snowflake
- Practical experience with at least one major cloud provider such as Azure, AWS, or GCP
- Experience with stream processing technologies including Kafka or Spark Structured Streaming
- Strong understanding of ETL/ELT patterns, data modelling, and data warehousing concepts
- Experience with orchestration tools such as Apache Airflow or Azure Data Factory
- Knowledge of Infrastructure as Code tools including Terraform
- Understanding of production-grade systems including observability, scalability, reliability, and performance
- Ability to independently lead technical initiatives from concept to delivery
- Strong communication and collaboration skills
- Upper-Intermediate or higher English level
WILL BE A PLUS
- Familiarity with RAG pipeline design and LLM integration patterns
- Knowledge of data governance frameworks and tools such as Unity Catalog or Apache Atlas
- Experience with dbt for data transformation and modelling
- Familiarity with MLflow, Feature Stores, or ML platform integrations
PERSONAL PROFILE
- Proactive and self-driven mindset
- Strong analytical and architectural thinking
- Ability to work independently and take ownership of technical decisions
- Passion for innovation and modern engineering practices
- Knowledge-sharing and team-oriented approach
- Strong problem-solving skills