Full-Stack Software Engineer
Core
Design, build, and maintain reliable and scalable data pipelines for batch and near real-time data processing to support analytics, BI, and reporting.
Role type
Data Engineer
Builds
Data pipelines, ELT/ETL workflows, and data models
Domain
Financial services / Data Engineering
Deliverable
production ML models
Required skills
SQL, Python, Cloud data platforms (AWS/Azure/GCP), Data warehouses (Snowflake/BigQuery/Redshift), ETL/ELT tools (dbt/Airflow/Fivetran), Data modeling, Git
Preferred skills
Distributed processing (Spark/Databricks), Streaming data (Kafka/Event Hubs/Kinesis), Data quality/observability tools, DevOps/IaC (Terraform/CI/CD), ML/GenAI data pipelines
Technologies
AWS, Azure, GCP, Snowflake, BigQuery, Redshift, Synapse, dbt, Airflow, Fivetran, Azure Data Factory, Spark, Databricks, Kafka, Event Hubs, Kinesis, Terraform
Responsibilities
Design and build scalable data pipelines for batch and near real-time processing; Develop and manage ELT/ETL workflows to ingest data from multiple sources; Build and optimize data models to support analytics and reporting; Ensure data quality, accuracy, and consistency through validation and monitoring; Collaborate with analysts, data scientists, and product teams to understand data requirements; Troubleshoot and resolve data pipeline failures and performance issues
Seniority
Mid-level, hands-on IC
