Junior Data Engineer

Roles and Responsibilities ● Assist in designing, developing, and maintaining ETL workflows and data pipelines using SQL Server, SSIS, and/or Azure Data Factory (ADF). ● Write and optimize SQL queries for data extraction, transformation, and loading. ● Support data storage, retrieval, and basic database maintenance in SQL Server environments. ● Work with different data sources and file formats such as CSV, JSON, XML, and Parquet. ● Assist in developing and maintaining reporting solutions in collaboration with BI teams. ● Monitor data pipelines and troubleshoot basic data quality, integration, and processing issues. ● Assist in identifying and resolving data inconsistencies to maintain data accuracy and integrity. ● Work with senior data engineers and cross-functional teams to understand data and reporting requirements. ● Document data pipelines, workflows, data sources, and processes. ● Support automation and data manipulation tasks using Python. ● Participate in testing, debugging, and improving existing data pipelines and ETL processes. Required Qualifications ● Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field. ● 1+ year of hands-on experience in data engineering, ETL, database development, or a related role. ● Good understanding of SQL, preferably with SQL Server. ● Basic hands-on experience with ETL tools such as SSIS and/or Azure Data Factory (ADF). ● Basic programming knowledge in Python for data manipulation and automation. ● Familiarity with common data formats such as CSV, JSON, XML, and Parquet. ● Basic understanding of data modeling, relational databases, and database design concepts. ● Basic exposure to reporting or BI tools such as Power BI and/or SSRS. ● Good analytical and problem-solving skills. ● Ability to work collaboratively in a team environment and willingness to learn new technologies. Preferred Skills ● Basic exposure to Azure Data Factory (ADF) and/or SQL Server Integration Services (SSIS). ● Familiarity with Power BI or other data visualization/BI tools. ● Some exposure to cloud platforms such as Azure, AWS, or GCP. ● Basic knowledge of Git or other version control systems. ● Basic understanding of Linux/Unix command-line environments. ● Familiarity with data ingestion and integration concepts. ● Basic understanding of data governance, security, and data quality practices. ● Strong willingness to learn and grow in the field of data engineering.