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Associate Data Operations

Pay
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Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Reconcile dbt borrowing base outputs against counterparty reports

  • Investigate and document root causes of variances

  • Resolve straightforward data issues independently and escalate complex ones

  • Monitor dbt pipeline runs and triage errors from logs and test failures

  • Build and maintain reconciliation checklists and validation procedures per facility

From the employer’s posting
Compare outputs from dbt borrowing base pipelines against counterparty reports
Investigate and document the root cause of variances, distinguishing between data quality issues, pipeline logic errors, and legitimate counterparty differences
Resolve straightforward data issues independently, including minor data corrections and known edge cases
Triage pipeline errors by reviewing logs and test failures, providing initial diagnosis before escalation
Develop and maintain reconciliation checklists and validation procedures for each borrowing base facility
Apply at Fortunize

Posting record

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Open 4 monthsWe first saw this posting 134 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 28, 2026134 days ago
Recorded sightings
62
Last seen by us
Nov 9, 2026
Employer says posted
Jun 25, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 134

Up longer than most. Similar jobs usually come down between day 3 and day 46.

From 404 similar postings that came down. Coming down is not always a hire.

Fortunize is hiring

6 open jobs

  • No new data jobs since July
  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Snowflake
  • pandas
Where the posting names them
As a Data Operations, you will serve as a critical quality control function within our data team. Your primary focus will be validating the outputs of our dbt-based borrowing base pipelines against counterparty reports, identifying discrepancies, and determining causes. You will work closely with our Analytics Engineering team to investigate and resolve data issues, ranging from straightforward fixes you handle independently to more complex problems requiring escalation with clear documentation. This role is foundational to building out our India-based data operations function. While you will start as a senior individual contributor, there is a clear path to growing and leading a team of 3-5 analysts as we scale. Responsibilities: Reconciliation & Validation Compare outputs from dbt borrowing base pipelines against counterparty reports to identify discrepancies in loan-level data, collateral values, and portfolio metrics Investigate and document the root cause of variances, distinguishing between data quality issues, pipeline logic errors, and legitimate counterparty differences Develop and maintain reconciliation checklists and validation procedures for each borrowing base facility Issue Resolution Resolve straightforward data issues independently, including minor data corrections and known edge cases For complex issues, prepare detailed documentation of findings and escalate to Analytics Engineers with clear context and recommendations Over time, contribute minor fixes and pull requests to dbt models as you develop deeper pipeline familiarity Pipeline Monitoring Monitor dbt pipeline runs and flag failures or anomalies to the appropriate team members Triage pipeline errors by reviewing logs and test failures, providing initial diagnosis before escalation Documentation & Communication Maintain clear records of reconciliation results, discrepancy resolutions, and recurring issues Communicate findings to Analytics Engineers, Operations, and other stakeholders in a clear, structured manner Coordinate with external counterparties as needed to resolve data-related questions Requirements What we are looking for: 4+ years of experience in data analysis, data quality, reconciliation, or a related role Advanced SQL skills with experience querying complex data sets and troubleshooting data issues Experience working with financial data sets (lending, FinTech, financial services, or related industries) Strong analytical and problem-solving skills with keen attention to detail Excellent written and verbal communication skills, with the ability to document findings clearly and explain technical issues to non-technical stakeholders Self-directed with the ability to work independently and manage priorities across multiple facilities Nice to Have: Familiarity with dbt (Data Build Tool) or willingness to learn quickly Experience with Snowflake or similar cloud data warehouses Exposure to Git workflows and version control basics Understanding of borrowing base mechanics, collateral management, or warehouse lending Python proficiency (Pandas or similar) for ad-hoc analysis Experience in a reconciliation, audit, or data quality assurance function

Your next step

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Demand for Data Operations roles

New Data Operations postings at the employers we follow are up 203% over the last 6 weeks compared with the 6 before.

Weekly new Data Operations postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 28, the most 274, and the latest week had 69.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Operations, by the work the posting describes.

Data operations staff do the day-to-day work of getting data processed correctly: loading and checking files, moving records between systems, fixing errors and following set procedures.

Expect Excel, some SQL, close attention to detail, and knowledge of the particular systems the company runs.

Data governance sets the rules for the data; data operations does the hands-on work of processing it and keeping it moving.

Job description

View original posting ↗

As a Data Operations, you will serve as a critical quality control function within our data team. Your primary focus will be validating the outputs of our dbt-based borrowing base pipelines against counterparty reports, identifying discrepancies, and determining causes. You will work closely with our Analytics Engineering team to investigate and resolve data issues, ranging from straightforward fixes you handle independently to more complex problems requiring escalation with clear documentation. This role is foundational to building out our India-based data operations function. While you will start as a senior individual contributor, there is a clear path to growing and leading a team of 3-5 analysts as we scale. Responsibilities: Reconciliation & Validation Compare outputs from dbt borrowing base pipelines against counterparty reports to identify discrepancies in loan-level data, collateral values, and portfolio metrics Investigate and document the root cause of variances, distinguishing between data quality issues, pipeline logic errors, and legitimate counterparty differences Develop and maintain reconciliation checklists and validation procedures for each borrowing base facility Issue Resolution Resolve straightforward data issues independently, including minor data corrections and known edge cases For complex issues, prepare detailed documentation of findings and escalate to Analytics Engineers with clear context and recommendations Over time, contribute minor fixes and pull requests to dbt models as you develop deeper pipeline familiarity Pipeline Monitoring Monitor dbt pipeline runs and flag failures or anomalies to the appropriate team members Triage pipeline errors by reviewing logs and test failures, providing initial diagnosis before escalation Documentation & Communication Maintain clear records of reconciliation results, discrepancy resolutions, and recurring issues Communicate findings to Analytics Engineers, Operations, and other stakeholders in a clear, structured manner Coordinate with external counterparties as needed to resolve data-related questions Requirements What we are looking for: 4+ years of experience in data analysis, data quality, reconciliation, or a related role Advanced SQL skills with experience querying complex data sets and troubleshooting data issues Experience working with financial data sets (lending, FinTech, financial services, or related industries) Strong analytical and problem-solving skills with keen attention to detail Excellent written and verbal communication skills, with the ability to document findings clearly and explain technical issues to non-technical stakeholders Self-directed with the ability to work independently and manage priorities across multiple facilities Nice to Have: Familiarity with dbt (Data Build Tool) or willingness to learn quickly Experience with Snowflake or similar cloud data warehouses Exposure to Git workflows and version control basics Understanding of borrowing base mechanics, collateral management, or warehouse lending Python proficiency (Pandas or similar) for ad-hoc analysis Experience in a reconciliation, audit, or data quality assurance function
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Hyderabad, Telangana, India

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