[Hiring] Junior Data Engineer @AHL - Saaf AI

Role Description

As a Data Engineer (Entry Level), you'll work closely with senior engineers to build and maintain data pipelines, write and optimize SQL, and support our cloud-based data warehouse. This role is ideal for freshers or engineers with up to 2 years of experience who want strong mentorship and hands-on exposure to modern data engineering tools and practices.

A Snapshot of Your Responsibilities

• Assist in building and maintaining data pipelines under the guidance of senior engineers.
• Write, test, and optimize SQL queries to extract, transform, and validate data.
• Support batch data ingestion and basic ETL/ELT workflows using Python.
• Help maintain data quality by running basic checks and flagging inconsistencies.
• Learn and work within our cloud data warehouse (Snowflake/Databricks) under supervision.
• Document your work — data flow notes, basic technical specs, and test cases.
• Participate in code reviews and incorporate feedback to improve code quality.
• Collaborate with analytics and business teams to understand data needs.
• Take a proactive approach to learning new tools, languages, and best practices.
• Communicate progress and blockers clearly with your team.

Qualifications

• For Freshers (0 years experience):
• Bachelor's degree in Computer Science, Computer Engineering, IT, or a related field.
• Basic understanding of SQL — able to write simple SELECT, JOIN, and aggregation queries.
• Basic knowledge of Python programming.
• Basic awareness of data warehousing concepts (tables, schemas, ETL at a conceptual level).
• Understanding of relational databases and data structures.
• Strong willingness to learn, good analytical thinking, and attention to detail.
• Good verbal and written communication skills.
• For 1–2 Years Experienced:
• 1–2 years of hands-on experience in a data engineering, analytics engineering, or similar role.
• Working knowledge of SQL, including joins, aggregations, and basic performance tuning.
• Hands-on experience with Python; exposure to PySpark is a plus.
• Exposure to a cloud data warehouse or lakehouse platform (Snowflake, Databricks, Redshift, or BigQuery).
• Basic exposure to ETL/data pipeline tools (e.g., Airflow, dbt, Fivetran) is a plus.
• Familiarity with version control (Git/GitHub/Bitbucket).
• Basic understanding of any cloud platform (AWS, Azure, or GCP).
• Good problem-solving skills and ability to work in an agile team environment.

Nice to Have

• Academic or internship project experience involving data pipelines or analytics.
• Exposure to workflow orchestration tools such as Airflow.
• Basic familiarity with streaming concepts (Kafka) or NoSQL databases.
• Exposure to BI/visualization tools (Power BI, Tableau, Looker).
• Basic knowledge of Docker or containerization concepts.