Data Engineer ||

Key Responsibilities

• Extract, clean, and load data from various structured and unstructured sources.
• Design, develop, and optimize data pipelines using Snowflake, SQL, Kafka, and related technologies.
• Investigate and document new data sets for analytical and operational use cases.
• Triage incoming bugs, incidents, and data issues, ensuring timely resolution.
• Perform technical operations tasks to maintain data pipeline performance.
• Troubleshoot and resolve issues related to data quality, pipeline failures, or latency.
• Participate in Agile ceremonies sprint refinement, planning, and estimation.
• Monitor key data flows and proactively raise awareness of potential issues.
• Define and implement data quality assurance rules to ensure data accuracy.
• Guide, onboard, and mentor Data Engineer I team members on technical best practices.

Required Skills and Qualifications

• Bachelors degree in Computer Science, Information Technology, or a related discipline.
• 3–5 years of professional experience in data engineering or ETL development.
• Strong proficiency in SQL (including query optimization and data modeling).
• Hands-on experience with

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  Snowflake (warehouse design, data ingestion, and transformations).
• Experience with Kafka or similar streaming technologies.
• Familiarity with data warehousing concepts and ETL workflows.
• Working knowledge of Python or Scala for data processing (preferred).
• Understanding of relational and non-relational data models.
• Excellent problem-solving, analytical, and collaboration skills.