Data Engineer

Role Summary

Support data architecture, infrastructure, and reporting ecosystem. Ensure reliable data pipelines, optimize cloud performance, and deliver high-quality data to business stakeholders and BI tools.

Infrastructure & Pipelines

- Maintain and optimize cloud-based data infrastructure

- Build, monitor, and troubleshoot ETL pipelines

- Ensure data pipeline reliability, quality, and timely delivery

- Implement data governance, security, and access controls

- Support infrastructure automation

Reporting & Analytics Support

- Design and maintain data models and reporting marts for BI tools

- Support business reporting needs and ad-hoc data requests

- Optimize query performance for dashboards and reports

- Maintain data documentation, dictionaries, and lineage

Required Skills

- SQL: Strong proficiency in Redshift/PostgreSQL, complex queries, performance tuning

- AWS: Hands-on with data-related infrastructure

- ETL/Orchestration: Experience with ETL processing tools (Airflow, Kafka Connect)

- Python: Data processing, automation, scripting

- Data Modeling: Star schema, dimensional modeling, data warehouse concepts

- BI Tools: Experience supporting Power BI, Looker, Qlik Sense, or similar

- Nice to have: Docker, ClickHouse, MongoDB, Elasticsearch, data quality frameworks

Requirements

- Bachelor's degree in Computer Science, IT, Engineering, or related field

- 2-4 years of experience in data engineering, infrastructure, or cloud operations

- Financial services or fintech background preferred

- Strong problem-solving and troubleshooting abilities