Junior Data Engineer
New
J
JobgetherData Engineering
IndiaFull-TimeJunior
Salary not disclosed
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Job Details
- Experience
- 1–2 years
- Required Skills
- AWSPythonSQLETLGCPGitSnowflakeAzureDatabricks
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field (for fresh graduates).
- 1–2 years of hands-on experience in data engineering, analytics engineering, or a similar role (for experienced candidates).
- Basic to working knowledge of SQL, including SELECT statements, JOINs, and aggregations.
- Basic to hands-on knowledge of Python programming.
- Understanding of relational databases, data structures, data warehousing concepts, tables, schemas, and fundamental ETL principles.
- Basic understanding of at least one cloud platform (AWS, Azure, or GCP).
- Strong analytical thinking, problem-solving ability, curiosity, and attention to detail.
- Ability to collaborate effectively and work within an Agile team environment.
- Exposure to PySpark is an advantage.
- Exposure to cloud platforms such as Snowflake, Databricks, Redshift, or BigQuery is preferred.
- Familiarity with version control systems (Git, GitHub, or Bitbucket) is preferred.
- Basic exposure to data pipeline or ETL tools such as Airflow, dbt, or Fivetran is a plus.
Responsibilities
- Assist senior engineers in building, maintaining, and improving data pipelines.
- Write, test, and optimize SQL queries to extract, transform, validate, and analyze data.
- Support batch data ingestion and basic Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows using Python.
- Perform basic data quality checks and identify, document, and flag inconsistencies or anomalies.
- Support the maintenance and operation of cloud-based data warehouse or lakehouse environments such as Snowflake and Databricks.
- Document data flows, technical specifications, test cases, and other relevant engineering processes.
- Participate in code reviews and apply feedback to improve code quality, reliability, and maintainability.
- Collaborate with analytics and business teams to understand data requirements and support data-related initiatives.
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