Junior Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Junior Data Engineer based in India.

This is an early-career opportunity to build practical data engineering skills while contributing to real-world data systems.
You will work closely with experienced engineers to develop and maintain pipelines that support analytics, reporting, underwriting insights, and AI-driven decision-making.
The role provides hands-on exposure to SQL, Python, ETL/ELT workflows, cloud data platforms, and modern data engineering practices.
You will also contribute to data quality, documentation, testing, code reviews, and collaboration with analytics and business teams.
Strong mentorship and feedback will help you develop your technical capabilities and confidence as an engineer.
The position is designed for fresh graduates as well as professionals with up to two years of relevant experience.
It is an excellent fit for a curious, analytical, and detail-oriented engineer who is eager to learn and grow in a remote environment.

• Assist senior engineers in building, maintaining, and improving data pipelines.
• Write, test, and optimize SQL queries for data extraction, transformation, validation, and analysis.
• Support batch data ingestion and basic ETL/ELT workflows using Python.
• Perform data quality checks, identify inconsistencies, and communicate potential data issues to the team.
• Learn and support cloud-based data warehouse and lakehouse environments, including Snowflake and Databricks.
• Document data flows, technical specifications, processes, and test cases clearly and accurately.
• Participate in code reviews and apply feedback to improve code quality and engineering practices.
• Collaborate with analytics and business teams to understand data requirements and support their needs.
• Proactively develop knowledge of new tools, technologies, programming languages, and data engineering practices.
• Communicate project progress, technical challenges, and blockers clearly with senior engineers and team members.
• Contribute to an agile engineering environment and continuously improve technical and problem-solving skills.

Requirements:

• For candidates with no professional experience: Bachelor’s degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• For freshers, basic SQL knowledge, including the ability to write SELECT, JOIN, and aggregation queries.
• Basic understanding of Python programming.
• Basic knowledge of data warehousing concepts, including tables, schemas, and ETL processes.
• Understanding of relational databases and fundamental data structures.
• Strong analytical thinking, attention to detail, curiosity, and willingness to learn.
• Good written and verbal communication skills.
• For candidates with 1–2 years of experience: 1–2 years of hands-on experience in data engineering, analytics engineering, or a similar role.
• Working knowledge of SQL, including joins, aggregations, and basic query performance tuning.
• Hands-on Python experience; exposure to PySpark is an advantage.
• Exposure to cloud data warehouse or lakehouse platforms such as Snowflake, Databricks, Redshift, or BigQuery.
• Basic experience with ETL and data pipeline tools such as Airflow, dbt, or Fivetran is a plus.
• Familiarity with version control systems such as Git, GitHub, or Bitbucket.
• Basic understanding of at least one major cloud platform, such as AWS, Azure, or GCP.
• Good problem-solving abilities and the ability to collaborate effectively within an agile team.
• Academic or internship projects involving data pipelines or analytics are valuable.
• Exposure to workflow orchestration tools such as Airflow, streaming concepts such as Kafka, or NoSQL databases is a plus.
• Familiarity with BI and visualization platforms such as Power BI, Tableau, or Looker is advantageous.
• Basic knowledge of Docker or containerization concepts is a plus.

Benefits:

• Full-time employment.
• Fully remote position based in India.
• Opportunity to work on real-world data systems supporting analytics, reporting, underwriting insights, and AI-driven decision-making.
• Close collaboration and mentorship from experienced data engineers.
• Hands-on exposure to modern data engineering tools and cloud data platforms.
• Opportunity to develop skills across SQL, Python, ETL/ELT, data quality, cloud infrastructure, and data warehousing.
• Exposure to Snowflake and Databricks environments.
• Opportunity to participate in code reviews and modern engineering practices.
• Collaboration with analytics and business teams.
• Strong learning and professional development opportunities for early-career engineers.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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