Associate Data Engineer

Jobgether; India; Hybrid; INR 420,000 - 640,000; Full time

Benefits offered by this job

Competitive compensation package

Health and wellness benefits

Paid time off and holidays

Flexible hybrid work arrangements

Learning and development opportunities

Exposure to cloud data platforms

Inclusive team culture

Professional development resources

Job summary

Jobgether on behalf of a partner company in India seeks an Associate Data Engineer to join a fast‑paced data engineering team. You’ll design and optimize ETL/ELT pipelines, work with Snowflake and Matillion, and participate in data ingestion from APIs and cloud storage.

This entry‑level role emphasizes hands‑on learning with tools like Airflow and AWS. You will contribute to data movement, transformation, and reliability for BI and analytics, while collaborating with engineers to deliver

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 0-1 years experience or related internships, projects, or certifications in data engineering.
• Strong SQL skills with joins, aggregations, and query optimization.
• Basic Python or scripting knowledge.
• Understanding of ETL/ELT concepts and data warehousing.
• Familiarity with Linux/Unix environments and command-line operations.
• Basic knowledge of cloud platforms, especially AWS services (S3, EC2, Lambda).
• Exposure to Snowflake, Matillion, or similar data integration platforms.
• Understanding of orchestration/scheduling tools like Airflow or cron.
• Familiarity with APIs and data formats such as JSON and CSV.
• Knowledge of Git version control.
• Strong analytical thinking, attention to detail, and problem-solving.
• Good communication and teamwork abilities.

Responsibilities

• Assist in designing, building, and maintaining ETL/ELT pipelines using Matillion or equivalent platforms.
• Work with Snowflake to store, process, and analyze data efficiently.
• Write and optimize SQL queries for large datasets to support analytics.
• Ingest and transform data from sources including APIs and cloud storage (S3).
• Monitor data workflows, troubleshoot issues, and ensure reliable job execution.
• Support automation of data processes using Airflow or cron.
• Maintain high data quality and reliability across pipelines.
• Collaborate with cross-functional teams to gather data requirements.
• Document data workflows and processes clearly.
• Continuously learn new tools and best practices in data engineering.

Skills

SQL

Python

Linux/Unix

AWS

S3

EC2

Lambda

Snowflake

Matillion

Airflow

cron

Git

APIs

JSON/CSV

ETL/ELT

Data warehousing

SQL optimization

Data troubleshooting

Communication

Education

Bachelor’s degree in Computer Science / IT

Tools

Snowflake

Matillion

Airflow

Git

AWS (S3, EC2, Lambda)

Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Associate Data Engineer in India. This role is an excellent opportunity for early-career professionals and fresh graduates who are passionate about working with data and building scalable data systems. You will join a dynamic data engineering environment where modern cloud technologies are used to design and optimize data pipelines. The position offers hands-on exposure to tools such as Snowflake, Matillion, AWS, and orchestration frameworks. You will contribute directly to the movement, transformation, and reliability of large-scale datasets that support business intelligence and analytics. Working closely with experienced engineers, you will gain practical experience in ETL/ELT development, SQL optimization, and cloud-based data platforms. The environment is fast-paced, collaborative, and focused on continuous learning and technical growth. This role is ideal for candidates eager to build a strong foundation in data engineering and grow into advanced technical roles.

Accountabilities

• Assist in designing, building, and maintaining ETL/ELT data pipelines using tools such as Matillion or equivalent platforms.
• Work with Snowflake to store, process, and analyze structured and semi-structured data efficiently.
• Write, optimize, and maintain SQL queries for large-scale datasets to support analytics and reporting needs.
• Perform data ingestion and transformation from multiple sources including APIs, cloud storage (S3), and databases.
• Monitor data workflows, troubleshoot issues, and ensure smooth execution of scheduled jobs and pipelines.
• Support automation and orchestration of data processes using tools such as Airflow, cron, or similar systems.
• Ensure high standards of data quality, consistency, and reliability across all pipelines.
• Collaborate with cross-functional teams to gather data requirements and deliver effective data solutions.
• Maintain clear and structured documentation for all data workflows and processes.
• Continuously learn and adapt to emerging tools, technologies, and best practices in data engineering.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 0-1 years of experience, including internships, academic projects, certifications, or hands‑on exposure in data engineering.
• Strong understanding of SQL, including joins, aggregations, and query optimization techniques.
• Basic knowledge of Python or other scripting languages.
• Understanding of ETL/ELT concepts and data warehousing principles.
• Familiarity with Linux/Unix environments and command-line operations.
• Basic knowledge of cloud platforms, especially AWS services such as S3, EC2, and Lambda.
• Exposure to tools such as Snowflake, Matillion, or similar data integration platforms.
• Understanding of orchestration and scheduling tools like Airflow or cron.Familiarity with APIs and data formats such as JSON and CSV.
• Knowledge of version control systems such as Git.
• Strong analytical thinking, attention to detail, and problem-solving abilities.
• Good communication skills and ability to work effectively in a collaborative team environment.
• Ability to quickly learn and adapt to new technologies in a fast‑paced setting.

Benefits

• Competitive compensation package aligned with industry standards.
• Health and wellness benefits designed to support overall well‑being.
• Paid time off, holidays, and supportive leave policies promoting work‑life balance.
• Flexible and hybrid work arrangements depending on team requirements.
• Learning and development opportunities including training programs, mentorship, and career growth support.
• Exposure to modern cloud data platforms and enterprise‑scale engineering environments.
• Inclusive, collaborative, and team‑oriented work culture.
• Employee engagement initiatives, recognition programs, and professional development resources.