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Hire vetted Data Platform Engineers who build the lakehouse and streaming platforms behind analytics and AI at national scale. Shortlist in 48 hours; working within 4 working days.
Fig. 01Cloud & Complex Systems
Data Platform Engineer
Cloud & Complex Systems
AvailabilityShortlist in 48 h
Vetted Data Platform Engineer profiles free to start within 4 working days of signature. Counts appear in bands (5–10, 10–20, 20+); below 5 a role shows “Shortlist in 48 h” instead of a number.
Indicative monthly rate per seat
| Level | Experience | From (USD / month) |
|---|---|---|
| Mid | 4–6 years | 4,670 |
| Senior | 6–9 years | 6,140 |
| Lead | 9+ years | 7,980 |
Quotation-based. VAT shown separately. View in SAR, AED, USD or EUR. Quotes valid for 30 days.
Includes the Cloud & Complex Systems practice rate of +5% on the base band.
Remote Pro Ai places vetted Data Platform Engineers who build the lakehouse and streaming platforms behind analytics and AI at national scale. They design Spark, Flink and Kafka platforms with governance and cost control, implement Iceberg or Delta with Unity Catalog access policies, and run them with SLAs and disaster recovery.
Your Data Platform Engineer designs Spark / Flink / Kafka platforms with governance and cost control, and automates platform provisioning and CI/CD for data workloads. Typical stack: Databricks, Snowflake, Kafka, Flink and Iceberg.
National data lakes, telecom analytics and banking data hubs across the Gulf are consolidating onto shared platforms, while AI programmes need governed, real-time data. Platform-level skills, running the infrastructure that data engineers build on, are scarcer than pipeline skills, which has made data platform engineering a rising specialism.
Illustrative profiles that mirror the vetted bench for this role. Names, employers, full gate scores and video introductions, where recorded, are shared after the click-through NDA.
Data Platform Engineer
Senior9 years
Remote Pro Ai Vetted Verify credential RP-1524
Data Platform Engineer
Lead13 years
Remote Pro Ai Vetted Verify credential RP-3143
Data Platform Engineer
Mid5 years
Remote Pro Ai Vetted Verify credential RP-4762
Illustrative profiles that mirror the vetted bench for this role, anonymised. Names, employers, full scores and credentials are shared after the mutual NDA in the booking flow.
Designs Spark / Flink / Kafka platforms with governance and cost control
Implements lakehouse formats, catalogues and fine-grained access
Automates platform provisioning and CI/CD for data workloads
Operates platforms with SLAs, observability and disaster recovery
Enables ML and BI teams with reusable data services
Toolset on our bench
We test each capability in a live technical assessment scored by a practice lead. Nothing on this list is taken from a CV.
Mid4–6 years
Delivers well-scoped work independently within your architecture and standards.
from USD 4,670/month
Senior6–9 years
Owns a component or workstream end to end, reviews code and mentors.
from USD 6,140/month
Lead9+ years
Sets technical direction, leads the squad and reports to your leadership.
from USD 7,980/month
We never place junior profiles. A practice lead confirms every level, so the band you buy is the scope you get.
Typical certifications held by our Data Platform Engineer bench: Databricks Platform Architect · Confluent Certified. We verify every certificate with the issuing body before a profile reaches you, and list verified credentials on each profile card.
Remote Pro Ai information security: ISO/IEC 27001 certification in progress (target Q2 2027) · SOC 2 Type II planned for 2027. Evidence and policies are in the Trust Center.
Not sure this is the right role? Describe the outcome you need and the Scope Agent maps it to roles, levels and a draft squad in minutes.
A transport operator, Dubai
smart-mobility data platform
7 engineers · 10 months
Real-time sensor ingestion, streaming analytics, operations dashboards and an open-data API in a UAE cloud region
MatchIQ™ is our vetting and matching engine: 3.4% of applicants pass 5 gates. The live assessment for this role tests the 5 capabilities above against a realistic task, not trivia.
Self-serve bookings receive a shortlist within 48 hours and enterprise requests get named candidates within 72 hours. After you approve a profile and sign, your specialist is working within 4 working days, whether the request is on the bench, off-bench or on-site. When fewer than 5 Data Platform Engineer profiles are on the bench, we shortlist from the wider vetted network in the same 48 hours.
Pricing is quotation-based and depends on level, hours and any on-site, clearance or data-residency needs. Current bands: Mid from USD 4,670/month · Senior from USD 6,140/month · Lead from USD 7,980/month. VAT is shown separately, quotes can be viewed in SAR, AED, USD or EUR, and every quotation is valid for 30 days. The Squad Builder shows your quote instantly.
Remote Pro Ai is contractually responsible for quality. Raise it at any time: a replacement starts within 4 working days; the full handover completes in under 14 days. Your first engagement also begins with a no-bill trial, one per company: 5 working days on self-serve bookings and 10 on enterprise contracts.
This role is offered at Mid, Senior and Lead level. We never place junior profiles. A practice lead confirms each specialist’s level through a live technical assessment and reference checks, so the band on your quotation reflects scope the person has already delivered rather than a job title on a CV.
A Data Engineer builds pipelines and models for specific use cases. A Data Platform Engineer builds and operates the shared platform those pipelines run on: compute, table formats, catalogues, access control, CI/CD, observability and disaster recovery. Larger data organisations need both roles.
Databricks and Snowflake, Kafka and Flink for streaming, Iceberg and Delta table formats, Airflow for orchestration and Unity Catalog for governance. Many engineers hold Databricks Platform Architect or Confluent certification, verified with the issuer before we share profiles. Engineers also handle migrations between platforms and table formats.
Engineers set cluster policies, autoscaling and job-level cost attribution, tune storage layouts and govern who can run what. Teams see their own spend and the platform team reviews heavy workloads regularly, so cost tracks value as usage grows. Unused clusters and stale tables are cleaned up automatically.
Yes. Engineers design reusable data services, feature tables and governed datasets that BI and ML teams both consume, with fine-grained access and lineage. One governed platform avoids parallel copies of data and keeps definitions consistent between dashboards and models. ML teams get reproducible training snapshots from the same platform.
Add this role to a squad, see your quote instantly, and hold profiles free for 72 hours.
Build your squad online
No card needed · 72 h free hold · No-bill trial: 5 working days self-serve, 10 in the Enterprise lane.
20 minutes with a solutions architect
No sales script.