Associate Data Engineer

Overview:

We are looking for a motivated and detail-oriented Associate Data Engineer to join our data team. This role is ideal for recent graduates or early-career professionals (up to 1 year of experience) with strong Python and SQL fundamentals and a genuine interest in data engineering, cloud technologies, and the modern data stack.

You will work alongside experienced data engineers on real-world projects, gaining hands-on experience in building data pipelines, processing data at scale, and working with cloud-based data platforms. This role offers structured mentorship and a clear growth path toward becoming a Data Engineer.

Key Responsibilities:

Data Processing and Pipelines

• Write clean, well-structured Python scripts for data processing, transformation, and automation.
• Assist in building and maintaining ETL/ELT pipelines and data workflows.
• Work with structured, semi-structured (JSON, CSV, Parquet), and unstructured data from multiple sources such as APIs, databases, and files.
• Perform data cleaning, transformation, and validation using libraries such as Pandas or Polars.

Databases and SQL

• Write and optimize SQL queries for data extraction, analysis, and transformation.
• Work with relational databases such as PostgreSQL, MySQL, or SQL Server.
• Assist in designing simple data models and database tables.

Data Quality and Support

• Help implement data quality checks to ensure accuracy and consistency.
• Monitor scheduled jobs and help troubleshoot pipeline failures and data issues.
• Support data integration activities across systems and teams.

Cloud and Tools Exposure

• Gain hands-on exposure to cloud data services on AWS, Azure, or GCP (such as S3, Azure Data Factory, or BigQuery).
• Learn and work with orchestration tools such as Apache Airflow and transformation tools such as dbt.
• Get introduced to modern data platforms such as Databricks, Snowflake, or Microsoft Fabric.

Collaboration and Learning

• Work closely with senior team members to understand requirements and deliver assigned tasks.
• Participate in code reviews, team discussions, and knowledge-sharing sessions.
• Maintain clear documentation of data processes, pipelines, and technical work.
• Continuously learn new tools, frameworks, and best practices in data engineering.

Required Skills:

• Strong understanding of Python fundamentals, including data structures, functions, file handling, and error handling.
• Good working knowledge of SQL, including joins, aggregations, GROUP BY, and subqueries.
• Basic understanding of relational databases and data modeling concepts (tables, keys, normalization).
• Basic understanding of data processing concepts and ETL/ELT workflows.
• Familiarity with working with data formats such as CSV, JSON, and Excel.
• Familiarity with Git and GitHub.
• Good analytical skills and attention to detail.
• Clear written and verbal communication.
• A strong willingness to learn and adapt quickly.

Good to Have:

• Hands-on experience with Pandas, NumPy, or Polars.
• Knowledge of advanced SQL concepts such as window functions and CTEs.
• Basic exposure to Apache Spark / PySpark.
• Familiarity with Airflow, dbt, or similar data tools.
• Basic exposure to a cloud platform (AWS, Azure, or GCP).
• Basic understanding of data warehousing concepts (fact and dimension tables, star schema).
• Familiarity with NoSQL databases such as MongoDB.
• Basic knowledge of Docker or Linux commands.
• Exposure to BI tools such as Power BI or Tableau.
• Relevant certifications (such as AWS Cloud Practitioner, Azure Data Fundamentals DP-900, or Databricks Fundamentals), Kaggle work, or hackathon participation.
• A GitHub profile or portfolio showcasing data or Python projects.

Educational Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related technical field.
• Academic, internship, or personal projects involving Python, SQL, databases, data engineering, or cloud technologies will be strongly considered.

What We’re Looking For:

• Strong fundamentals, a solid educational background, and a logical, problem-solving mindset.
• Candidates who can clearly explain their academic or personal projects, including the data they worked with, the tools they used, and what they learned.
• Curiosity, attention to detail, and the ability to learn quickly in a fast-evolving field.
• Extensive professional experience is not required; we value potential, attitude, and a passion for working with data.

Pay: ₹300,000.00 - ₹450,000.00 per year

Benefits:

• Health insurance
• Leave encashment
• Provident Fund

Work Location: In person