Data Engineer

We are looking for a hands-on Data Engineer who is strong in SQL and Python, can build efficient data pipelines, and is comfortable working with Snowflake, IICS, and cloud-based data platforms. The team is also open to candidates from related technical backgrounds, as long as they are familiar with the tools and can learn quickly, and they are comfortable using AI tools to support development work.

Responsibilities

• Design, develop, and maintain data pipelines, transformations, and orchestration workflows that ingest, curate, and publish data for analytics use cases.
• Build and enhance data models based on business analysis and reporting requirements.
• Work with structured and semi-structured data from enterprise systems and files, including relational databases, JSON, and XML.
• Collaborate with Data Analysts, source-system developers, and business stakeholders to define requirements and deliver fit-for-purpose data solutions.
• Improve engineering productivity by using AI tools for code support, testing framework creation, documentation, diagramming, and solution exploration.
• Support data quality, performance optimization, maintainability, and operational reliability of data solutions.
• Enable business reporting, self-service analytics, and foundational data assets for advanced analytics and data science teams.
• Follow established organizational standards for governance, security, access control, and data handling.

Qualifications

• Minimum of 5-7 years’ hand-on experience.
• Background in programming, databases, data engineering, analytics engineering, or related technical disciplines; or degree in computer science, software engineering, information systems, economics, or other relevant engineering fields.

Technical Competencies

• Strong SQL and Python skills.
• Hands-on experience with Snowflake and ETL/ELT or data integration platforms; IICS experience is strongly preferred.
• Experience with data orchestration and workflow tools; familiarity with Airflow is a plus.
• Experience with data transformation and modeling tools such as dbt or equivalent frameworks.
• Familiarity with CI/CD practices, version control, and testing approaches for data solutions.
• Experience working with relational databases such as SQL Server and PostgreSQL.
• Ability to work with APIs and semi-structured data formats such as JSON and XML.
• Understanding of cloud and DevOps concepts is a plus.
• Ability to adapt to evolving tools, platforms, and AI-assisted engineering practices.