Assistant Manager

Junior Data Engineer

We are seeking a motivated and detail-oriented Junior Data Engineer to join our growing data team. In this role, you will support the design, development, and maintenance of data pipelines, data integration processes, and analytical data platforms. You will work closely with senior data engineers, data analysts, data scientists, and business stakeholders to ensure reliable, high-quality data is available for reporting, analytics, and business decision-making.

This is an excellent opportunity for candidates looking to build a career in data engineering and gain hands-on experience with modern data technologies, cloud platforms, and big data solutions.

Delivery of reliable and scalable data pipelines. High data quality and accuracy standards. Timely resolution of data issues. Effective collaboration with cross-functional teams. Continuous learning and adoption of best practices.

Develop, maintain, and monitor ETL/ELT data pipelines. Extract, transform, and load data from various source systems into data warehouses and data lakes. Assist in building and optimizing data models for analytics and reporting. Perform data validation, cleansing, and quality checks to ensure data accuracy. Support data integration efforts across multiple systems and platforms. Write and optimize SQL queries for data extraction and analysis.

Troubleshoot data pipeline issues and implement fixes under guidance. Collaborate with data analysts, data scientists, and business teams to understand data requirements. Document data flows, technical processes, and data lineage. Follow data governance, security, and compliance standards. Participate in code reviews and contribute to continuous improvement initiatives.

Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field. 1–2 years of experience in data engineering, software engineering, or data-related roles. Strong understanding of SQL and relational databases. Basic programming knowledge in Python, Java, or Scala. Understanding of ETL concepts and data integration processes. Familiarity with data warehousing concepts and dimensional modeling. Knowledge of version control tools such as Git.

Strong analytical and problem-solving skills. Excellent communication and teamwork abilities.

Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with data engineering tools such as Apache Spark, Airflow, Databricks, or Kafka. Exposure to Snowflake, Redshift, Big Query, or Synapse. Understanding of REST APIs and data ingestion techniques. Knowledge of CI/CD practices and Dev Ops fundamentals. Relevant certifications in cloud or data technologies.

SQL Python Data Modeling Fundamentals ETL/ELT Concepts Relational Databases (SQL Server, PostgreSQL, MySQL) Git

• Attention To Consistency
• D3 Data Visualization
• Internal Communications
• Interpersonal Relationship Building
• Leadership Capabilities
• Marketing Acumen
• Programming Fundamentals
• Working under Pressure