Senior Data Engineer

We are looking for a Senior Data Engineer to join our Data Engineering Team and take ownership of high-impact, greenfield data initiatives. You will work on building modern cloud-native data platforms, migrating on-premises legacy systems to the cloud, and laying the architectural foundation for AI-ready data infrastructure.

In this role, you will collaborate closely with Machine Learning, Data Science, and Product teams, serving as a key technical contributor and thought leader. You will also drive R&D efforts around agentic AI architectures, event-driven systems, and LLM-ready data pipelines – turning architectural concepts into production-grade solutions.

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 Py.

Spark 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 Py.

Spark 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