Mid Data Analyst
Indexed description
The Role
We are looking for a mid-level Data Analyst to join a small team to support the migration of data from Domo to Google BigQuery and Looker, with potential alternative delivery into AWS QuickSight. This role will focus on rebuilding existing Domo dataflows, ensuring continuity of reporting for business users.
Key Responsibilities
Migration from Domo
- Analyse existing Domo dataflows (Magic ETL, datasets)
- Rebuild in BigQuery (Looker) and/or AWS Redshift (for QuickSight)
- Ensure parity between legacy (Domo) and new platform outputs
- Support phased decommissioning of Domo Data
- Prepare datasets for consumption in: Looker (third party data), QuickSight (internal data)
- Support semantic layer development
- Ensure consistency with existing reporting logic
- Reconcile outputs between Domo and target platforms during migration
- Identify and resolve data quality issues
- Document transformations and logic clearly
- Work closely with a small team
- Engage with business stakeholders where required
- Provide pragmatic input into cross-platform decisions
- Strong SQL (BigQuery, Redshift, or similar warehouse)
- Experience building ETL/ELT pipelines in cloud environments
- Hands-on experience with Domo (Magic ETL / datasets) OR similar legacy BI tooling
- Experience with BigQuery and/or AWS Redshift
- Understanding of data modelling for BI/reporting
- Experience with Looker / LookML
- Experience with AWS QuickSight
- Python (or similar) for data processing
- Experience with data platform migrations
- Exposure to music / media / rights data (nice to have)
- Interest in AI/LLM use cases (e.g. chat over data, semantic querying)
- Ability to help prepare datasets for AI-driven exploration
- Not core to role, but relevant to upcoming workstreams
- Mid-level Data Analyst (comfortable working independently within defined scope)
- Pragmatic and delivery-focused
- Able to operate across multiple tools/platforms where required
- Comfortable in a small, fast-moving team
- Successful migration of priority datasets from Domo to BigQuery and/or AWS stack
- Reliable, documented pipelines replacing legacy workflows
- Clean, reusable data models supporting Looker and/or QuickSight
- Minimal disruption to existing reporting during transition
With flexible remote options, diverse projects, and access to development resources, joining Ness means building a career that’s meaningful and impactful.
What To Expect Next
We believe great experiences start with transparency—and that includes our hiring process. Here’s what you can typically expect after you hit "Apply":
- HR Interview – A conversation to get to know you better and align on expectations.
- Technical Interview – A chance to showcase your skills and experience.
- Client Interview – Ensuring mutual fit between you and the client team.
- Offer Stage – If everything aligns, we’ll be happy to make it official.
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