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About the role
Education, Knowledge, Experience 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. Experience working with data warehousing, data marts, reporting environments, and cloud-based data platforms. Experience building ETL/ELT pipelines and supporting analytics-focused data solutions
Functional Competencies Knowledge of data and analytics frameworks supporting data lakes, warehouses, marts, and reporting. Strong understanding of data modeling principles and the ability to design solutions aligned with business objectives. Experience using AI for data engineering tasks such as design support, testing, documentation, structured prompting, and workflow improvement. Ability to work across the data lifecycle, from ingestion and transformation through delivery of trusted analytical data sets. Understanding of data quality, validation, monitoring, retention considerations, and operational support requirements. Ability to balance modern engineering practices with strong core data development fundamentals. Strong collaboration and communication skills when working with analysts, developers, and business stakeholders.
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.
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