About the Job

We’re hiring a Data Engineer to help design, build, and scale reliable data pipelines and analytics-ready datasets. This is a Full-time role with a Hybrid work arrangement. You’ll partner with data consumers, engineers, and stakeholders to turn business requirements into secure, performant ETL workflows—supporting reporting, insights, and data-driven decision-making. If you enjoy working end-to-end on data systems (from ingestion to transformation to delivery) and thrive in collaborative environments, this role is for you.

Roles & Responsibilities

• Develop and maintain ETL pipelines for ingesting, transforming, and delivering data to downstream users.
• Implement scalable data transformations using PySpark, with efficient processing and clear, maintainable code.
• Build and optimize jobs in Databricks, ensuring stable orchestration and strong performance.
• Design data models and integration logic for relational systems, including PostgreSQL and other required data sources.
• Write and tune queries in Apache Hive to support large-scale batch processing and warehouse workloads.
• Collaborate with teams to define data quality checks, validation rules, and reliable SLAs for pipelines.
• Troubleshoot data issues, monitor pipeline health, and continuously improve reliability and throughput.
• Document architectures, pipelines, and engineering decisions to support long-term maintainability.

Required Skills & Qualifications

• Strong proficiency in Python for data processing, automation, and pipeline development.
• Hands-on experience with ETL development and production data pipeline practices.
• Demonstrated experience with Databricks and distributed data processing workflows.
• Solid working knowledge of PySpark, including performance optimization techniques.
• Proficiency with PostgreSQL, including schema design and query performance fundamentals.
• Experience with Apache Hive and batch processing/warehouse-style workloads.
• Ability to translate requirements into technical designs and deliver robust, testable data solutions.