Fujitsu is Hiring Junior Data Engineer | Pune | Freshers

Job Description

Fujitsu's Junior Data Engineer opening is a genuinely accessible entry point into data engineering, worth distinguishing clearly from more advanced "Data Engineer" listings that quietly expect production pipeline-building experience. This role is explicitly framed as 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴, 𝗳𝗶𝗿𝘀𝘁-𝗹𝗲𝘃𝗲𝗹 𝗰𝗵𝗲𝗰𝗸𝘀, 𝗮𝗻𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 — you'd be watching over existing data pipelines, catching failures, validating outputs, and escalating complex issues to senior engineers, rather than designing or building new data infrastructure yourself. This is a meaningfully different (and lower-barrier) role than a typical "Data Engineer" title might suggest.

This matters for how you should approach applying: if you're picturing yourself writing complex ETL pipelines or working extensively in Spark/Databricks from day one, recalibrate — that's listed only under "good-to-have," not core requirements. The 𝗰𝗼𝗿𝗲 𝘀𝗸𝗶𝗹𝗹 𝘀𝗲𝘁 𝗵𝗲𝗿𝗲 𝗶𝘀 𝗰𝗹𝗼𝘀𝗲𝗿 𝘁𝗼 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀/𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘄𝗼𝗿𝗸 𝗮𝗽𝗽𝗹𝗶𝗲𝗱 𝘁𝗼 𝗮 𝗱𝗮𝘁𝗮 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 — ServiceNow ticket management, basic SQL validation, log collection, and documentation are the daily bread-and-butter, with the data engineering concepts layered on top as domain knowledge rather than hands-on building.

For candidates newer to data engineering specifically, this is actually a reasonable and realistic way in — you'd build genuine exposure to production data systems, incident management processes, and pipeline monitoring at a large enterprise scale, without needing advanced ETL development skills upfront. The "good-to-have" list (AWS S3/Glue, Snowflake, Databricks, Python) signals where Fujitsu wants you to grow into over time, giving a fairly clear roadmap for what to self-study once you're in the role.

𝗢𝘂𝗿 𝗧𝗮𝗸𝗲:

- 𝗚𝗼𝗼𝗱 𝗳𝗼𝗿: CS/IT graduates newer to data engineering who want genuine production data systems exposure without needing advanced pipeline-building skills upfront; also good for those who prefer structured, supervised work under senior engineers rather than high autonomy from day one

- 𝗡𝗼𝘁 𝗶𝗱𝗲𝗮𝗹 𝗳𝗼𝗿: those specifically seeking hands-on ETL pipeline design or advanced cloud data engineering work — this role is monitoring/support-focused, with pipeline building explicitly outside the core scope

- 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗱𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁𝘆: likely lower relative to more advanced data engineering listings — the core skill bar (basic SQL, ETL concepts, ticketing) is genuinely achievable for freshers, making this a good realistic first step rather than a highly competitive specialized role

- 𝗖𝗮𝗿𝗲𝗲𝗿 𝘁𝗿𝗮𝗷𝗲𝗰𝘁𝗼𝗿𝘆: commonly leads into Data Engineer, ETL Developer, or Cloud Data Engineer roles as you build hands-on pipeline experience beyond the initial monitoring/support scope — worth treating this explicitly as a stepping-stone role rather than a long-term destination if pipeline development is your ultimate goal

𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝗻𝘁𝗲𝘅𝘁: Fujitsu hasn't disclosed pay for this role. Junior Data Engineer/production support roles at large global IT companies in Pune typically range around ₹3–4.5 LPA for freshers, based on general market data for comparable support-focused data roles — this is an estimate only, and is likely on the lower end of "data engineering" titled roles specifically because of the support/monitoring nature of the actual work.

𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Since the core requirements are genuinely basic (SQL, ETL concepts, ticketing familiarity), your realistic differentiator is demonstrating any exposure to the "good-to-have" list — even a personal project touching AWS S3, basic Python scripting, or a free-tier Snowflake trial — since that signals initiative beyond the minimum bar and aligns directly with where Fujitsu likely wants this role to grow over time.

Roles & Responsibilities

The responsibilities are structured around watching, checking, and escalating rather than building — a genuinely operational role supporting existing data infrastructure under senior engineer supervision.

- Monitor scheduled data pipeline runs, job status, alerts, and data refresh activities

- Perform first-level checks for failed jobs, missing files, incomplete loads, and data mismatches

- Create, update, and track incidents and service requests in ServiceNow

- Run basic SQL queries to validate job outputs and support source-to-target reconciliation

- Collect logs, screenshots, and error details before escalating complex issues to senior resources

- Assist with documentation, runbooks, SOPs, and daily status updates

Qualifications & Eligibility

No explicit degree requirement is stated in this posting, though the listing notes both relocation and visa sponsorship are not supported — worth confirming you're already positioned in or near Pune before applying, since this rules out relocation assistance for out-of-city candidates.

- Basic understanding of SQL, data engineering concepts, and ETL/ELT processes

- Works under the supervision of intermediate and senior engineers

- No relocation or visa sponsorship provided

Skills Required

Core skills are operational/support-focused; the good-to-have list points toward genuine cloud data engineering tools worth self-studying to grow beyond this role.

- Core: Basic SQL, ETL/ELT concepts, data validation, pipeline monitoring, incident management, ServiceNow, documentation

- Good-to-have: AWS S3/Glue awareness, Snowflake/Databricks awareness, Python basics, SFTP basics, CloudWatch or equivalent monitoring tools