Job Overview

Fujitsu is hiring for a Junior Data Engineer opportunity based in Pune. The role focuses on supporting day-to-day data engineering operations, including pipeline monitoring, first-level troubleshooting, data validation, incident updates, documentation, and production support. It is designed for someone building practical experience in data engineering and who has a basic understanding of SQL, ETL or ELT processes, monitoring, and operational support.

In this position, you will work under the guidance of intermediate and senior engineers while helping keep data pipelines and related applications running smoothly. Your work will involve checking scheduled jobs, investigating common data issues, validating outputs, recording incidents, and preparing useful technical information when a problem needs to be escalated.

This is a good opportunity for candidates who want to develop a foundation in data operations while gaining exposure to cloud and modern data platforms. The job listing identifies Pune as the job location and also states that location flexibility may be available across multiple locations in the country. Relocation support and visa sponsorship are not provided according to the listing.

Key Responsibilities

• Monitor scheduled data pipelines, job executions, alerts, incoming files, and data refresh activities.
• Perform initial checks when jobs fail, files are missing, loads are incomplete, or data does not match expected results.
• Create, maintain, and follow up on incidents, service requests, tasks, and change requests using ServiceNow.
• Use basic SQL queries to inspect data, validate outputs, and assist with source-to-target reconciliation.
• Gather logs, screenshots, error messages, and other technical details before escalating complex incidents to senior engineers.
• Help maintain operational documentation such as runbooks, standard operating procedures, checklists, status reports, and knowledge-transfer material.
• Support routine production activities, monitoring reports, and operational reporting under the direction of experienced team members.

Required Skills

The core technical foundation for this role includes basic SQL knowledge and an understanding of data engineering concepts. Candidates should be familiar with ETL and ELT processes and understand why data needs to be extracted, transformed, loaded, validated, and monitored.

You should also understand basic data validation and pipeline monitoring practices. The role involves incident management and production support, so the ability to follow troubleshooting steps, identify common issues, collect useful evidence, and escalate problems clearly is important.

ServiceNow knowledge is relevant because the role requires regular updates to tickets and operational requests. Candidates should also be comfortable preparing technical documentation and operational reports in a clear and structured way.

Preferred Skills

The job listing identifies several technologies and areas as good-to-have skills. These include file-based data ingestion, SFTP basics, AWS S3, AWS Glue, Snowflake, Databricks, Python, and CloudWatch or similar monitoring tools.

Direct experience with every preferred technology is not required by the listing. Familiarity with even a few of these areas can help candidates understand modern data pipelines and cloud-based data operations. A willingness to learn is particularly useful because the position involves developing knowledge of data engineering support processes.

Education

The provided job description does not specify a mandatory degree, academic discipline, or certification requirement. Candidates should therefore present their relevant education, training, coursework, projects, or practical learning related to SQL, data engineering, databases, cloud platforms, or data processing where applicable.

Experience

The job description does not provide a specific minimum or maximum number of years of professional experience. The position is described as a junior-level role, with day-to-day activities performed under the supervision of intermediate and senior engineers. Candidates who are starting a career in data engineering or have relevant academic, project, internship, or practical exposure may find the responsibilities aligned with an early-career path, subject to the employer's selection criteria.

Required Technologies

The main technology areas mentioned for this opportunity are SQL, ETL, ELT, ServiceNow, SFTP, AWS S3, AWS Glue, Snowflake, Databricks, Python, and CloudWatch.

Candidates should understand that the role is broader than programming alone. Data pipeline monitoring, data validation, incident management, production support, operational reporting, documentation, and troubleshooting are important parts of the technical environment.

Soft Skills

Attention to detail is important because the role involves checking data, monitoring pipeline activity, identifying mismatches, and recording incident information accurately. Good communication is also valuable when preparing escalation details or sharing status information with senior engineers.

Candidates should be comfortable following established procedures, asking questions when information is unclear, learning from experienced colleagues, and documenting work consistently. A collaborative attitude and willingness to learn new technologies can help you succeed in a junior data engineering environment.

Benefits of Working in this Role

This role can provide practical exposure to data engineering operations and production environments. You can build experience in pipeline monitoring, SQL-based validation, incident handling, operational documentation, and troubleshooting while working alongside more experienced engineers.

The opportunity can also help you understand how data systems are supported in a business environment. Exposure to AWS services, Snowflake, Databricks, monitoring tools, and production processes can broaden your understanding of modern data platforms as your responsibilitis grow.

Work Mode

The provided job description does not explicitly specify onsite, hybrid, or remote work mode. Candidates should confirm the current work arrangement with Fujitsu during the application rocess.

Location

The primary job location is Pune, Maharashtra, India. The listing also states that there is location flexibility across multiple locations in the country. It specifically states that relocation support is not provided and visa sponsorship is not approved.

Who Should Apply

This opportunity is suitable for candidates interested in starting or developing a career in data engineering, data operations, production support, or data platform support. Applicants should be comfortable with basic SQL and interested in understanding ETL or ELT pipelines, monitoring, data validation, and operational troubleshooting.

Candidates with academic projects involving databases, SQL, ETL workflows, cloud storage, Python, or data analysis can highlight those projects on their resumes. Familiarity with ServiceNow or similar ticketing systems is also useful.

Career Growth

A junior data engineering support role can provide a foundation for future positions such as Data Engineer, ETL Developer, Data Operations Engineer, Cloud Data Engineer, Production Support Engineer, or Data Platform Engineer. Developing stronger SQL skills, learning Python, understanding data architecture, and gaining hands-on experience with cloud and modern data platforms can support long-term progression.

Application Advice

When applying, emphasize practical examples rather than listing technologies without context. Highlight SQL projects, data pipeline exercises, ETL or ELT work, database assignments, cloud projects, Python scripts, or monitoring-related experience if you have them.

Be prepared to explain how an ETL or ELT pipeline works, how you would investigate a failed job, how SQL can be used to validate data, and what information should be collected before escalating an incident. Understanding the difference between data validation, monitoring, incident management, and production support can also help you prepare for interviews.