Data Engineer
Core
Design, build, and optimize scalable Lakehouse data solutions on AWS to unify data warehousing and data lake capabilities for enterprise analytics and advanced machine learning models in the financial sector.
Role type
Senior Data Engineer (Cloud & MLOps)
Builds
Scalable Lakehouse architectures, high-throughput ETL/ELT pipelines, automated feature engineering pipelines, and production ML model deployments.
Domain
Financial Services / Banking / Cloud Data Engineering
Deliverable
production ML models | product features
Required skills
AWS data services (S3, Glue, EMR, Redshift), PySpark, Apache Kafka, SQL, Python, Databricks, Delta Lake, Terraform, Docker, Kubernetes (EKS), CI/CD pipelines
Preferred skills
AWS certifications, Apache Flink, Spark Streaming, Apache Airflow, Prefect, Scala
Technologies
AWS, Databricks, Delta Lake, PySpark, Apache Kafka, Terraform, GitHub Actions, AWS SageMaker, MLflow, Docker, EKS
Responsibilities
Design and optimize Lakehouse architectures; Develop batch and real-time ETL/ELT pipelines; Optimize query performance and storage efficiency; Support Machine Learning & MLOps workflows; Enforce banking-grade data security and governance; Automate infrastructure and deployment pipelines.
Seniority
Senior, hands-on IC