Mid-Level Data Engineer
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Job Description
Professional Data Engineer developing and maintaining robust data solutions using SQL and Python. Collaborating with data science and analytics to ensure data quality and integrity across platforms.
Responsibilities:
- Develop and maintain ETL pipelines using SQL and/or Python.
- Use tools like Dagster/Airflow for pipeline orchestration
- Collaborate with cross-functional teams to understand and deliver data requirements.
- Ensure a consistent flow of high-quality data using stream, batch, and CDC processes.
- Use data transformation tools like DBT to prepare datasets to enable business users to self-service.
- Ensure data quality and consistency in all data stores.
- Monitor and troubleshoot data pipelines for performance and reliability.
Requirements:
- 3+ years of experience as a data engineer.
- Proficiency in SQL is a must
- Experience with modern cloud data warehousing, data lake solutions like Snowflake, BigQuery, Redshift, Azure Synapse.
- Experience with ETL/ELT, batch, streaming data processing pipelines.
- Excellent ability to investigate and troubleshoot data issues, providing fixes and proposing both short and long-term solutions.
- Knowledge of AWS services (like S3, DMS, Glue, Athena, etc.)
- Familiar with DBT or other data transformation tools.
- Familiarity with GenAI, and how to leverage LLMs to resolve engineering challenges.
- Experience with orchestration tools like Dagster, Airflow, AWS Step functions, etc.
- Familiar with CI/CD pipelines and automation.
Benefits:
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
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