Data Engineer

Data Engineer
#офис
Company: Gsrmarkets
Salary: $80k - $95k estimated
☑️Your responsibilities may include:
-Design and evolve core data models and services that standardise trade, market, pricing, risk and finance data across streaming, lake/lakehouse and warehouse layers.
-Build and operate streaming and batch pipelines to capture orders, quotes, trades and market data; reconcile sources; and deliver trusted, versioned datasets for analytics, risk and finance.
-Implement robust data quality, lineage, governance and access controls; define SLAs/SLOs and data contracts to ensure reliability and auditability.
-Manage cloud‑based storage and processing (AWS preferred), optimizing for cost, performance and scalability; support time‑series and dimensional analytics.
-Develop monitoring, alerting, anomaly detection and playbooks for incident response, backfills and reprocess/replay.
-Partner with stakeholders across Front Office, Risk, Finance, Business Development, Operations and Compliance to translate requirements into pragmatic data products; document, review and continuously improve tooling and processes.

☑️What We’re Looking For
-8+ years in data engineering within financial markets. Experience in at least one of Front Office (Sales & Trading), Risk Management, Finance, Business Development, Operations, or Compliance is required.
-Strong programming in Python, Java and SQL; experience with Rust is a plus.
-Proven track record architecting streaming and batch ETL/ELT at scale using modern data pipeline and messaging technologies.
-Solid understanding of market/trade data lifecycles and time‑series concepts, or equivalent experience working with financial datasets.
-Hands‑on with a major cloud platform (AWS preferred) and cloud‑native data services; experience operating lake/lakehouse and warehouse architectures.
-Strong grasp of data governance, security and data quality practices, including lineage, cataloging and role‑based access.
-Demonstrated ability to deliver high‑reliability systems with clear SLAs, efficient backfill/replay strategies and cost/performance optimization.
-Excellent communication skills with the ability to align technical and non‑technical stakeholders.
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