Data Engineer

We are looking for a Data Engineer to help build and maintain reliable data solutions for a client. This position focuses on moving, transforming, and validating data from multiple sources to support reporting, analytics, and operational needs. The ideal candidate will be comfortable working with modern cloud data platforms, collaborating with cross-functional teams, and improving data processes for accuracy, consistency, and timely delivery.

Responsibilities:

• Design, develop, and maintain data pipelines that ingest information from APIs, files, network sources, and other internal or external systems.

• Build and enhance automated data workflows using Snowflake, Azure Data Factory, Python, and SQL to support reporting and analytics needs.

• Apply business rules to transform raw data into structured, usable datasets for analysts, stakeholders, and downstream applications.

• Partner with business users, analysts, developers, and project teams to gather requirements and deliver data solutions within an agile environment.

• Monitor data quality by validating, cleansing, and reconciling datasets to ensure dependable and consistent information availability.

• Troubleshoot pipeline failures, data inconsistencies, and integration issues, then implement fixes to improve system stability.

• Maintain clear documentation for data warehouse configurations, workflow logic, and processing standards.

• Manage code and workflow changes through version control practices to support traceability and controlled deployment.

• Improve the timeliness and efficiency of data delivery for internal teams and third-party data consumers by identifying process enhancements.

Requirements

• 2+ years of experience in data engineering, ETL development, or a closely related data integration role.

• Hands-on experience using Python and SQL to transform, query, and prepare data for business use.

• Working knowledge of Snowflake and its associated data loading or orchestration capabilities.

• Experience with Azure Data Factory for connecting sources and building data movement workflows.

• Background in importing, extracting, transforming, and piping data from APIs, flat files, and other structured data sources.

• Ability to investigate data issues, perform quality checks, and support reliable production data processes.