Senior Data Engineer

🔥 0 minutes ago

🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

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73 Strings

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

💳 Fintech

💸 Finance

🤖 Artificial Intelligence

Fintech • Finance • Artificial Intelligence

73 Strings is a global FinTech firm shaping the future of how illiquid assets are analyzed, valued, and monitored utilizing augmented intelligence solutions for valuation and analytics. The company offers a comprehensive platform that integrates data extraction, portfolio monitoring, and valuations, empowering alternative asset managers with real-time insights and AI-driven analytics. Their technology aims to transform data complexity into strategic advantages, providing clients in private equity, venture capital, private credit, and infrastructure with the tools needed for accurate and efficient valuation processes.

📋 Description

• Build and operate pipelines, integrations and warehouse supporting valuation and monitoring • Own production pipelines from source capture through transformation, reconciliation and client delivery • Put pipelines under GitHub, automated testing and CI/CD • Help redefine platform architecture across ingestion, processing and delivery • Build and operate batch and streaming pipelines from databases, APIs, event streams and semi-structured sources • Implement change data capture and incremental loading, including ordering, deletes, replay and slowly changing dimensions • Build medallion datasets and dimensional models for Snowflake, Microsoft SQL Server and Databricks • Apply data contracts, reconciliation and row-level quarantine before publication • Own GitHub workflow and CI/CD, including tests, review, environment promotion and deployment as code • Investigate production data failures • Translate requirements from product, valuation and client-facing teams into operable pipelines

🎯 Requirements

• 10+ years in data engineering on production systems • Snowflake or Databricks as a primary platform, including modelling, performance tuning and cost management • Python and SQL for pipeline development and testing • Change data capture and event processing, including ordering, replay and schema change • Azure, including Databricks, ADLS and private network connectivity • GitHub and CI/CD for data workloads, using GitHub Actions or an equivalent system • Data quality, reconciliation, monitoring and production incident response • Experience building multi-tenant, secure data platforms, including tenant isolation, access control and data protection • Desirable: Databricks Lakeflow, Auto CDC, Declarative Automation Bundles and DQX, or Snowflake equivalents including Dynamic Tables, Streams and Tasks, Snowpark, Snowflake CLI deployments and Data Metric Functions • Debezium, Kafka Connect or Confluent Kafka • Apache Airflow or an equivalent workflow orchestrator • Kafka or Spark Structured Streaming, Apache Iceberg or Delta Sharing, and dbt for analytical models on curated data • Private markets data: valuations, funds, portfolio companies or capital activity • Comfortable working directly with client technical teams and collaborating across field engineering, product and other stakeholders

🏖️ Benefits

• Supportive culture of innovation and collaboration • Opportunities to take initiative and learn continuously

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