Trading Data Platform Lead

AlphaRebate

. Lead development, maintenance, and reliability of a data platform ingesting data from trading servers, bridges, and liquidity-provider feeds .

Posted 9/24/2026full-timeLimassol • CyprusSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining production data platforms, with a strong focus on ClickHouse and Snowflake for data transformation and storage. Proficient in implementing engineering practices such as CI/CD, monitoring, and data quality controls to ensure data integrity and reliability.

Highest-signal resume keywords

ClickHouse ExpertiseProduction Snowflake ExperiencePython ProficiencyAdvanced SQL SkillsData Platform Ownership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data TransformationData Quality ControlSchema Change GovernanceVersion ControlCI/CDMonitoringData ModelingReconciliation ProcessesPerformance TuningData Pipeline Development

Soft Skills

Clear Written CommunicationKnowledge TransferCross-Training

Tools & Technologies

AirflowDagsterKafkaDbt

Industry Keywords

Trading Data FluencyFinancial MarketsTransactional DatasetsQuantitative AnalysisMarket Maker

Tech Stack

Tools & technologies

AirflowKafkaPythonRustSQLC++Go

About the role

Key responsibilities & impact

Lead development, maintenance, and reliability of a data platform ingesting data from trading servers, bridges, and liquidity-provider feeds
Transform, store, and serve data through ClickHouse and Snowflake
Establish and maintain reconciliation processes across source systems and data environments
Identify variances and document and escalate material discrepancies
Develop and maintain monitoring, data-quality controls, schema-change governance, alerting, and operational procedures across production components
Establish engineering practices including version control, CI/CD, testing, code review, and documentation for data pipelines and infrastructure
Design scalable and reusable data solutions for evolving analytical and reporting requirements across IC Companies
Work with quantitative, technology, and analytical teams to translate requirements into reliable and performant data models and solutions
Maintain data integrity and quality
Maintain documentation, knowledge transfer, and cross-training so multiple team members can operate and support data-platform processes and services
Work alongside quant researchers and quant developers
Report to the Head of the Intelligence function

Requirements

What you’ll need

Bachelor’s or higher degree in Computer Science, Software Engineering or a related engineering discipline, or equivalent demonstrable experience building and operating production data systems
Several years owning a production trading data platform at a broker, proprietary trading firm, market maker, bridge or trading-technology vendor, or exchange-adjacent business
Deep, hands-on ClickHouse experience, including MergeTree engine family, deduplication and FINAL semantics, partitioning, TTL, materialized views, and performance tuning under high-cardinality tick and trade data
Production Snowflake experience
Production orchestration and streaming experience with Airflow or Dagster, Kafka, change-data-capture, version-controlled transformations using dbt or equivalent, and CI/CD for data
Trading data fluency covering deals versus positions, partial closes, netting and hedging accounts, swaps and commissions, symbol and contract mapping, server time versus UTC, rollover and weekend edge cases, MT4/MT5 server data structures, bridge and LP fill logs, and FIX drop copies
Experience building and running platform-to-warehouse reconciliations
Strong Python
Advanced SQL proficiency
Clear written communication for runbooks, data contracts, and incident write-ups
Experience in financial markets or a comparable environment preferred
Experience with complex transactional or financial-market datasets and associated analytical systems preferred
Systems-language experience in Go, Rust, or C++ preferred
Prior experience strengthening a fragile, complex, or single-operator data environment preferred

Benefits

Comp & perks

Competitive pay
22 days of annual leave
12 paid sick days
Full medical insurance coverage after 6 months
Group Savings and Life Insurance Plan after 6 months
Fully stocked kitchen with fresh fruit, snacks, and beverages
Daily lunch buffet
Paid overtime
Dedicated learning and development budgets
Referral bonus
Team events and team-building activities
MadBenefits employee perk platform with discounts on dining, retail, entertainment, and everyday essentials
Access to gym facilities, organized sports, and spa treatments
Unwind Fridays with a relaxed drink with colleagues