Role :

We are looking for an experienced Data Engineering professional with strong expertise in designing, building, and owning scalable data platforms. The ideal candidate will have hands-on experience in data architecture, data modeling, ETL/ELT development, and production-grade data pipeline management, with a strong focus on data quality, auditability, and governance.

The role requires expertise in Python and SQL along with experience handling finance, risk, or compliance-related data environments where accuracy, lineage, and traceability are critical.

Data Engineering & Architecture :

- 6+ years of Data Engineering experience.

- Strong understanding of data architecture and distributed data systems.

- Experience making design decisions around scalability, partitioning, performance optimization, and data storage strategies.

- Proven track record of owning production-grade data platforms.

SQL :

- Expert-level SQL skills.

- Strong experience with Window Functions, Common Table Expressions (CTEs), CASE Statements, Query Optimization, Complex Joins, and Cross-dialect SQL (MySQL & PostgreSQL).

Python :

- Expert-level Python development.

- Hands-on experience with Pandas, SQLAlchemy, Type Hints, Dataclasses, Object-Oriented Programming, and Class-based ETL/Data Pipelines.

Data Modeling :

- Fact and Dimension Modeling, Star & Snowflake Schema Design, Normalization Techniques, Medallion Architecture, and Transaction Data Modeling.

Orchestration & DevOps :

- Airflow or similar orchestrators, Git Version Control, and CI/CD Pipelines.

Nice to Have :

- Apache Spark, Hive, Hadoop Ecosystem, and Large-scale Data Processing Frameworks.

Key Responsibilities :

- Design and implement end-to-end data pipelines using modern ETL/ELT frameworks to ensure high data availability and integrity for internal and external stakeholders.

- Optimize existing data warehouse architectures to improve query performance and reduce latency for complex analytical workloads.

- Collaborate with software engineering teams to integrate data ingestion services into existing product platforms, ensuring seamless data flow across the enterprise.

- Implement data governance and security best practices to maintain compliance and protect sensitive information across all data assets.

- Mentor junior engineers through code reviews and technical guidance to foster a culture of engineering excellence and continuous improvement.