Solidus Labs
Data Integration Analyst

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
At Solidus, we are shaping the financial markets of tomorrow by providing cutting-edge trade surveillance technology that protects investors, enhances transparency, and ensures regulatory compliance across traditional financial assets and crypto markets.
With over 20 years of experience in developing Wall Street-grade FinTech, our team delivers innovative solutions that financial institutions and regulators worldwide rely on to detect, investigate, and report market manipulation, financial crime, and fraud. Headquartered in Wall Street, with offices in Singapore, Tel Aviv, and London, we safeguard millions of retail and institutional entities globally, monitoring over a trillion events each day.
Role Overview
The Data Integration Analyst owns the end-to-end onboarding and normalization of external data into the platform's standardized schema and aligning an updated schema where new paradigms are identified. The role sits at the intersection of clients, data vendors, product and R&D, translating heterogeneous source feeds — client trade data, market data, and other reference/vendor feeds — into a consistent, load-ready format that powers downstream market inspection and surveillance algorithms.
This role is characterized by a highly detail-oriented, analytical, and service-minded individual who is comfortable moving between technical specification and client-facing communication. Success means external data is mapped faithfully, gaps are surfaced and resolved early with R&D, and every feed is validated end to end before it reaches production.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Onboard client trade data (orders and executions): specify it to the normalized target format and transmission method (flat file / SFTP, API, Kafka JSON, FIX, etc.), map source fields to the standardized schema, and align the feed to the standard load process.
- Coordinate and integrate market data feeds: scope the requirement per use case (including Level 1 vs Level 2 depth), align with vendors to attain data, map relevant fields to the standardized format, and surface any schema gaps with relevant stakeholders.
- Handle other data feeds (news/corporate events, client reference data, other vendor feeds), working the specification and adapter/mapping with the product team and R&D.
- Drive each integration end to end with R&D and the client — from initial sample through validated ingestion, confirming correctness in UAT before promoting to production.
- Maintain mapping documentation and source-to-target references, monitor feed health and data quality, flag anomalies, and feed learnings back into the process.
Requirements:
Must-Have
- Bachelor's degree in Information Systems, Industrial/Software Engineering, Computer Science, Data Analytics, or a related field — or equivalent practical experience.
- 5+ years in a data integration, data analyst, support, technical onboarding, or business/operations analyst role.
- High attention to detail and a structured, methodical approach to data mapping and validation.
- Strong analytical skills; comfort working with structured data, schemas, field-level mapping, and tabular formats (e.g., CSV, XML, JSON).
- Excellent communication and stakeholder management; able to bridge technical and business conversations with both R&D and clients.
- Strong service orientation and ownership — able to drive an integration from specification through to validated, end-to-end delivery.
- Exposure to data integration / ETL / adapter development workflows.
- Scripting or query experience (e.g., Python, SQL) for inspecting and transforming data.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
Nice-to-Have
- Experience with financial / market data or trading systems and their data requirements.
- Familiarity with Level 1 vs Level 2 market data and order/execution lifecycle concepts.
Why This Role Matters
The platform's surveillance and inspection capabilities are only as reliable as the data feeding them. Incorrectly mapped fields, the wrong market data depth, or schema gaps directly degrade detection quality. This role is critical because it ensures every external source — trade, market, and reference data — is normalized accurately, scoped correctly by entitlement, and validated end to end, so that the algorithms operate on trustworthy, consistent inputs.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location