73 Strings
73 Strings
73 Strings एक वैश्विक फिनटेक कंपनी है जो तरलता-रहित परिसंपत्तियों के विश्लेषण, मूल्यांकन और निगरानी के लिए ऑगमेंटेड इंटेलिजेंस तकनीक विकसित करती है। इसका प्लेटफ़ॉर्म डेटा निष्कर्षण, पोर्टफोलियो निगरानी और मूल्यांकन कार्यप्रवाहों को एक साथ लाता है, ताकि वैकल्पिक परिसंपत्ति प्रबंधक जटिल वित्तीय डेटा को समय पर उपयोगी जानकारी में बदल सकें। कंपनी निजी इक्विटी, वेंचर कैपिटल, निजी ऋण और बुनियादी ढाँचे के क्षेत्र की फर्मों को सेवाएँ देती है तथा एआई-आधारित विश्लेषण के माध्यम से अधिक कुशल और सूचित मूल्यांकन प्रक्रियाओं में सहायता करती है।

Senior Data Engineer at 73 Strings — Hybrid, India

Lead secure batch and streaming data pipelines for 73 Strings’ private-capital valuation platform. Work across Azure, Databricks, Snowflake, and CI/CD infrastructure.

विवरण

  • Develop and run pipelines, integrations, and warehouse systems that support valuation and monitoring
  • Take ownership of production data flows from source capture through transformation, reconciliation, and client delivery
  • Manage GitHub-based workflows with automated testing and continuous integration and deployment
  • Contribute to evolving the platform architecture across ingestion, processing, and delivery layers
  • Create and operate batch and streaming pipelines using databases, APIs, event streams, and semi-structured data
  • Implement change data capture and incremental loading with support for ordering, deletions, replay, and slowly changing dimensions
  • Develop medallion architecture datasets and dimensional models in Snowflake, Microsoft SQL Server, and Databricks
  • Enforce data contracts, reconciliation checks, and row-level quarantine before data publication
  • Own data-workload GitHub processes and CI/CD, including testing, code review, environment promotion, and infrastructure-as-code deployment
  • Diagnose production data incidents and convert product, valuation, and client requirements into reliable operational pipelines

आवश्यकताएँ

  • At least 10 years of experience engineering data systems in production
  • Expertise with Snowflake or Databricks as a primary platform, including data modelling, performance tuning, and cost management
  • Proficiency in Python and SQL for developing and testing pipelines
  • Experience with change data capture and event processing, including ordering, replay, and schema evolution
  • Practical Azure experience with Databricks, ADLS, and private network connectivity
  • Experience using GitHub and CI/CD for data workloads through GitHub Actions or an equivalent platform
  • Knowledge of data quality, reconciliation, monitoring, and production incident response
  • Experience building secure, multi-tenant data platforms with tenant isolation, access controls, and data protection
  • Preferred: Databricks Lakeflow, Auto CDC, Declarative Automation Bundles, and DQX, or comparable Snowflake capabilities
  • Preferred: Debezium, Kafka Connect, or Confluent Kafka
  • Preferred: Apache Airflow or a comparable workflow orchestrator
  • Preferred: Kafka or Spark Structured Streaming, Apache Iceberg or Delta Sharing, and dbt
  • Preferred: Experience with private-markets data such as valuations, funds, portfolio companies, or capital activity
  • Ability to work directly with client technical teams and collaborate with field engineering, product, and other stakeholders

लाभ

  • A supportive working environment
  • Room to take initiative and lead improvements
  • Ongoing opportunities for professional learning
  • A collaborative team culture

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