We are looking for a motivated and detail-oriented Associate Data Engineer to join our Data Engineering team. The ideal candidate will assist in designing, developing, and maintaining data pipelines, integrating data from multiple sources, and ensuring the availability, quality, and reliability of data for analytics and business intelligence. This role is ideal for fresh graduates and early-career professionals looking to build a career in data engineering.
Key Responsibilities
- Develop, maintain, and optimize data pipelines for data ingestion and transformation.

- Extract, transform, and load (ETL/ELT) data from various sources into data warehouses or data lakes.

- Monitor data pipelines and resolve data processing issues.

- Ensure data quality, integrity, and consistency across systems.

- Write efficient SQL queries for data extraction, validation, and analysis.

- Work with structured and semi-structured data from multiple data sources.

- Collaborate with data analysts, software engineers, and business stakeholders to understand data requirements.

- Support the design and implementation of scalable data architectures.

- Assist in data modeling and database optimization.

- Maintain documentation for data pipelines, workflows, and data models.

- Participate in Agile/Scrum ceremonies and contribute to continuous process improvement.

Required Skills
- Basic understanding of SQL and relational databases.

- Knowledge of ETL/ELT concepts and data integration.

- Familiarity with programming languages such as Python, Java, or Scala.

- Understanding of data warehousing concepts and data modeling.

- Basic knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud.

- Familiarity with version control systems like Git.

- Strong analytical, problem-solving, and debugging skills.

- Good communication and collaboration abilities.

Preferred Skills
- Experience with ETL tools such as Apache Airflow, Talend, Informatica, or Azure Data Factory.

- Familiarity with big data technologies such as Apache Spark, Hadoop, or Kafka.

- Knowledge of cloud data platforms such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.

- Understanding of data lake and lakehouse architectures.

- Basic knowledge of scripting for automation.

- Exposure to DevOps or CI/CD practices for data engineering.

Educational Qualification
- Bachelor's degree in Computer Science, Information Technology, Data Science, Electronics, or a related engineering discipline.

Experience
- 0-2 years of experience in Data Engineering, ETL Development, Database Development, or a related field.

- Fresh graduates with strong SQL and programming fundamentals are encouraged to apply.