Time since we first saw it
Day 35
Similar jobs usually come down between day 6 and day 59.
At Sun King, jobs usually come down by about day 58.
From 740 similar postings that came down, and 12 of Sun King’s. Coming down is not always a hire.
Reads like a Data Governance role: data quality and governance.
New Delhi, Delhi, India
Live, first seen by us 35 days agoEmployment type Permanent - Full TimeRead the full posting
Document business rules and turn them into automated checks across services
Run the exception dashboard that tracks open data breaks and their age
Diagnose reported data issues to find whether the pipeline or the app caused them
Build CRM business, product and system reliability dashboards
Conduct usage, funnel and cohort analysis and design and analyse A/B tests
Document the business rules our systems are supposed to obey, turn them into automated checks that catch contradictions across services
run the exception dashboard that keeps every open break visible and ageing
work out whether the pipeline or the application caused it
Build the CRM's business and product dashboards.
Conduct usage, funnel, and cohort analysis; understand feature adoption through application data and Firebase; design and analyse A/B tests
You might be a strong candidate if you have/are - A bachelor’s degree in engineering. - 4+ years of relevant experience in product analytics, data quality, or business intelligence.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 35
Similar jobs usually come down between day 6 and day 59.
At Sun King, jobs usually come down by about day 58.
From 740 similar postings that came down, and 12 of Sun King’s. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
- Diagnose the reported data issues by starting from a symptom, checking in the CRM, querying read replicas, Grafana logs, CDC topics and work out whether the pipeline or the application caused it. - Bring together data from new sources yourself and run one-time analysis in Python and Redshift, handing over persistent pipelines to data engineering. - Build the CRM's business and product dashboards. Work from canonical warehouse tables and the company's standard metric and dimension definitions, helping define what each means for the CRM.
- A track record of finding a problem nobody asked you to look for, and getting it fixed afterwards. - Strong hands-on experience in SQL against messy production data, strong in Python. - Experience with Redshift or another columnar warehouse, Postgres databases, NoSQL databases like MongoDB.
- Hands-on experience with Google Analytics and Firebase, not just aware of them. - Understanding of how to pull data from a source that wasn't in the warehouse yet — an API, a vendor export, a production database — and loaded it yourself to answer a question. Doing this in AWS (RDS, S3) is a plus; querying ELB logs is a bonus. - Knowledge of PromQL, or the equivalent in Datadog, Grafana or New Relic, to build system reliability dashboards.
- Understanding of how to pull data from a source that wasn't in the warehouse yet — an API, a vendor export, a production database — and loaded it yourself to answer a question. Doing this in AWS (RDS, S3) is a plus; querying ELB logs is a bonus. - Knowledge of PromQL, or the equivalent in Datadog, Grafana or New Relic, to build system reliability dashboards. - Understanding of how to use AI tools to build small automations and dashboards outside the BI tool.
- Understanding of change data capture and event streaming (Kafka) — enough to reason about replication lag, not to build the pipeline. - Knowledge of a data quality framework — dbt tests, Great Expectations, Soda, Monte Carlo or similar. - Pay-as-you-go, asset finance, microfinance or emerging-market lending.
- Unstructured investigative querying across the warehouse, read replicas, Prometheus metrics and product events — spot-checking against source, sanity-checking new data, and chasing numbers that look wrong. - Diagnose the reported data issues by starting from a symptom, checking in the CRM, querying read replicas, Grafana logs, CDC topics and work out whether the pipeline or the application caused it. - Bring together data from new sources yourself and run one-time analysis in Python and Redshift, handing over persistent pipelines to data engineering.
Good to have: - Understanding of change data capture and event streaming (Kafka) — enough to reason about replication lag, not to build the pipeline. - Knowledge of a data quality framework — dbt tests, Great Expectations, Soda, Monte Carlo or similar.
- Experience with Redshift or another columnar warehouse, Postgres databases, NoSQL databases like MongoDB. - Experience with BI or dashboarding tool, preferably Looker — enough to build and maintain a production dashboard set other people depend on. - Experience managing A/B tests and done funnel and cohort analysis.
- Strong hands-on experience in SQL against messy production data, strong in Python. - Experience with Redshift or another columnar warehouse, Postgres databases, NoSQL databases like MongoDB. - Experience with BI or dashboarding tool, preferably Looker — enough to build and maintain a production dashboard set other people depend on.
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New Data Governance postings at the employers we follow are up 176% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 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.
We file this job under Data Governance, by the work the posting describes.
Data governance staff keep a company's data accurate, documented and used within the rules. They agree what key fields mean, set up quality checks, track who owns each dataset and look after master data.
Postings ask for SQL, a governance tool such as Collibra or Informatica, knowledge of privacy and data rules, and a lot of work with other teams.
A data engineer builds the systems that move data; governance staff set and check the standards that data has to meet.
Permanent - Full Time
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New Delhi, Delhi, India
Job location: Remote in India About the role: Sun King is looking for a Senior Product Analyst to be the analytical backbone of the CRM product team within Enterprise Products. In this role, you will sit close to the product managers, backend and data engineers, working at the intersection of product analytics and data reliability. You will help the team understand how the product is actually used and where it falls short, and you will be among the first to notice when the numbers behind those judgements cannot be trusted. The role will suit someone with technical depth who prefers to collaborate and work closely to a product and its users, is comfortable operating within an established data platform but can also do analysis from new data sources.
No clear work-authorization passage found. Eligibility is unconfirmed.