Data Engineer

Key Responsibilities:Develop, maintain, and troubleshoot data pipelines using Apache Airflow, Python, and SQL/PLSQL Manage and optimize data workflows for ETL, data cleaning, and transformation across multiple data sources and targets Collaborate with the architect to evaluate design options and build scalable, high-quality solutions Perform data administration tasks including scripting (PowerShell), database health checks, and optimization Work closely with stakeholders to understand analytical requirements and translate them into data solutions Support data warehouse integration, Qlik dashboards, and associated backend components Conduct root cause analysis and troubleshoot across the entire data flow (ETL to UI) Ensure adherence to coding standards, best practices, and QA guidelines Identify potential blockers early and proactively coordinate with cross-functional teamsEducation, Experience and Skills Required:Bachelor of Science Degree in Computer Science, Information Technology, Management Information Systems, Business or another relevant field AND a minimum of 3 years relevant experience OR equivalent combination of education and relevant experience Fluency in English is required Strong hands-on experience in Airflow and Python for orchestrating and developing data workflows Proficiency in SQL and PL/SQL for querying and transforming data Familiarity with Linux environments, PowerShell scripting, and Docker containers Solid understanding of data administration tasks, including backups, permissions, schema updates, etc. Experience in ETL development and data cleaning/validationNice to Have / Bonus Skills:Exposure to Qlik (QlikView/Qlik Sense) or other BI tools Experience working with Data Warehouses (Snowflake, Redshift, BigQuery, etc.) Familiarity with Jupyter Notebook for exploratory data analysis or prototypingKey Traits We're Looking For:Proactive communicator who can engage with architects, stakeholders, and team members effectively Detail-oriented problem solver who can troubleshoot end-to-end data flows Self-driven and accountable—comfortable owning development deliverables Able to see the big picture, not just code-level tasks

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