About the Role:
We are seeking a motivated and enthusiastic Data Engineer with 0-2 years of experience, including recent graduates, to join our growing data team. This is a fantastic opportunity to kickstart your data engineering career and contribute to building and maintaining our data infrastructure. You will work closely with senior engineers and data scientists, gaining valuable experience in a real-world setting. A strong foundation in Python and SQL is essential.
Responsibilities:
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Assist in the design, development, and maintenance of data pipelines using Python and SQL.
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Learn and apply ETL processes to transform and load data from various sources.
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Contribute to building and optimizing data warehouses and data lakes.
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Participate in data quality checks and monitoring to ensure data accuracy.
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Collaborate with data scientists and analysts to understand their data needs.
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Develop and maintain basic documentation for data processes.
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Learn and apply best practices for data engineering.
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Proactively identify and report potential data issues.
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Contribute to improving our engineering practices.
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Participate in code reviews and learn from experienced engineers.
Required Skills:
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Strong foundation in Python programming, including data manipulation libraries (e.g., Pandas, NumPy).
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Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server).
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Basic understanding of data warehousing concepts.
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Eagerness to learn and apply new technologies.
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Strong problem-solving and analytical skills.
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Excellent communication and collaboration skills.
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Ability to work independently and as part of a team.
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Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Preferred Skills:
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Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
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Experience with ETL tools and technologies (e.g., Apache Airflow).
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Familiarity with big data technologies (e.g., Hadoop, Spark).
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Experience with data visualization tools (e.g., Tableau, Power BI).
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Knowledge of data governance and security best practices.