Big Data Engineer openings in Bhubaneswar's Infocity tech park don't come up every day, and this one covers a full-time, on-site role paying up to ₹108,000 a month. It sits in the Data Engineering & BI category, working on the pipelines that move raw data from source systems into the reports and dashboards the rest of the business actually uses.
What the work looks like
The job splits fairly evenly between building things and keeping existing things running. On any given week, that means:
- Building and maintaining data pipelines using Hadoop and Apache Spark to move large volumes of raw data into usable structures
- Transforming that raw data into structured reports that business stakeholders can actually read and act on
- Building and updating dashboards, adjusting them as stakeholder questions shift over time
- Maintaining existing reporting workflows so they keep running as source data changes shape
- Optimizing slow queries so reports load in seconds rather than minutes during peak usage
A pipeline that ran fine for months can break the moment an upstream system changes its schema without warning. Last quarter, a vendor's sales feed silently switched a date field from one format to another, and every downstream report using that field started showing numbers that were technically correct but effectively meaningless until someone traced it back three pipeline stages upstream.
Finding that kind of issue usually starts with a stakeholder noticing a number looks off, not with an automated alert catching it first. Building better monitoring into the pipelines is an ongoing project for the team, and this role is expected to contribute to it as a normal part of the job.
Skills
Hands-on experience with Hadoop, Apache Spark, SQL, and either Python or Scala is required, along with real experience designing data pipelines rather than just running ones someone else built. Business stakeholders don't care which of these tools sits underneath a report, but getting from raw data to something they can trust takes all of them working together. Deep specialization in just one of these- say, someone who's spent years purely on Spark performance tuning without touching orchestration or business-facing reporting- would need to round out the rest fairly quickly to keep up with the full scope of this role.
A few additional skills would make an application stronger. Familiarity with cloud data platforms such as AWS EMR or Databricks is increasingly important each year, as fewer companies want to manage their own Hadoop clusters. Experience with a workflow orchestration tool like Apache Airflow speeds up how quickly someone becomes useful on this specific pipeline setup. Direct exposure to a BI tool such as Power BI or Tableau helps, too, since understanding how a dashboard is actually consumed changes how someone builds the pipeline that feeds it.
Education and experience
Computer science, information technology, or a comparable technical bachelor's degree is expected going in, though nothing about the specific discipline named on a diploma gets scrutinized much beyond that broad category. Four years of hands-on experience is what the listing calls for, enough time to have already made and fixed a few of the mistakes that come with running production data pipelines at scale. Someone coming from a pure BI background with little pipeline-building experience would likely need a few months to get comfortable with Spark and Hadoop specifically, even with SQL fundamentals already in place.
Pay and benefits
The role pays up to ₹108,000 a month for a big data engineer position in Bhubaneswar, which sits toward the upper end for this specialization in the city. Health insurance, paid time off, and provident fund contributions come standard, and the relocation package tends to matter more here than it would in a bigger metro, since much of the specialized data engineering talent this employer wants isn't currently based in Odisha.
- Relocation assistance for candidates moving to Bhubaneswar
- Accommodation support while settling into the city
Naukri Mitra has tracked a steady rise in data engineering postings out of Bhubaneswar's Infocity corridor over the past couple of years, largely driven by IT service companies expanding their analytics practices beyond the traditional Tier-1 hubs.
Where it's based
The position is on-site at Infocity, Chandrasekharpur, Bhubaneswar, Odisha, PIN code 751024. This isn't a remote role, and candidates specifically browsing big data engineer job openings in Bhubaneswar should plan for daily on-site presence at the Infocity campus. For someone weighing this against similar postings in Hyderabad or Pune, the salary here is lower in absolute terms, but Bhubaneswar's cost of living narrows that gap considerably once rent and daily expenses are factored in.
How the team works
The data team here is small enough that a single engineer often owns a pipeline end-to-end, from ingestion through to the dashboard a stakeholder actually opens each morning. That ownership model means less specialization than a larger company might offer, but it also means visible impact happens faster, since there's no ten-person chain between writing a fix and seeing it reflected in a report someone relies on.
New engineers typically spend their first month pairing with someone senior on an existing pipeline before taking ownership of anything independently. Bugs found during that period get treated as learning opportunities, since the pipelines here are complex enough that nobody fully understands every corner of them without spending real time in the code.
The broader analytics team, spread across a few different reporting functions, meets every other week to compare notes on which dashboards are actually getting used versus which ones quietly stopped mattering to anyone. Engineers on this team sit in on those conversations, which keeps pipeline work tied to something a business stakeholder genuinely needs rather than a data set nobody checks anymore.
Applying
Interested candidates should apply through the standard process attached to this listing, including a resume that specifically highlights pipeline work rather than general data analysis, since that distinction matters for this particular role. Interviews typically include a technical discussion walking through how a candidate would design a pipeline for a specific data scenario, rather than abstract questions about big data concepts in general.
