Posted 4 hours ago
Senior Data Engineer
@ 73 Strings
Toronto, Ontario
Requirements summary:
- Investigate production data failures, and turn requirements from product, valuation and client-facing teams into operable pipelines.
- 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.
Source and dates
Employer career site / ATS feed · teamtailor
- Employer posting date
- 2026-11-12
- First seen by our source
- 2026-11-12
- Source record updated
- 2026-11-12
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
73 Strings
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Revolutionizing Valuations and Portfolio Monitoring with AI and Advanced Data Intelligence.
Full company description
73 Strings is an award-winning agentic AI company transforming private capital operations through intelligent data extraction, portfolio monitoring, and valuation automation. Its AI-powered platform unifies fragmented investment workflows in a secure environment, enabling investment professionals to access trusted insights, automate processes, and make faster decisions. Trusted by 9 of the 10 global alternative asset managers, 73 Strings supports clients managing $20T+ in combined assets under management (AUM) across Private Equity, Private Credit, Growth Equity, Venture Capital, and Infrastructure. In 2025, the company raised $55 million in Series B funding from strategic investors including Goldman Sachs, Blackstone, Hamilton Lane, Golub Capital, 7RIDGE, and Broadhaven Ventures. Our AI-augmented solutions address the private capital industry’s most complex operational challenges: • 73 Intelligence: Our award-winning agentic AI platform unifies data extraction, portfolio monitoring, and valuation workflows into a single intelligent ecosystem, creating a trusted source of truth for investment teams. • 73 Extract: Converts unstructured portfolio data into structured, decision-ready intelligence with 99% data extraction accuracy, replacing manual processes with scalable AI automation. • 73 Monitor: Delivers real-time portfolio intelligence through automated analytics, dynamic visualizations, and scalable performance monitoring. • 73 Value: Digitizes and automates valuation workflows for private equity and private credit, delivering audit-ready valuations with advanced analytics, scenario modeling, and workflow automation. Powered by cutting-edge AI, 73 Strings delivers valuations up to 10x faster, cuts operational costs by up to 50%, achieves 99% data extraction accuracy, and provides enterprise-grade security, scalability, and reliability with SOC 1 and SOC 2 certification. Learn more at www.73strings.com.
- LinkedIn followers
- 38,548
- People associated on LinkedIn
- 339
- Reported office locations
- 575 Lexington Ave, New York, NY 10022, US
- 55, Rue La Boétie, Paris, Île-de-France 75008, FR
- 68 King William Street, London, England EC4N 7HR, GB
- 17l 18th Cross Road, Bengaluru, Karnataka 560076, IN
- RRAA7229 Innovation Boulevard Al Aqeeq Dist. 13519, Riyadh, SA
- 535 Mission St, San Francisco, California 94105, US
- 71 Robinson Road, Singapore, Central Region 068895, SG
- ADGM Square, Al Sila Tower, Al Maryah Island, Abu Dhabi, AE
- Jubilee Hills, Mahaveer Radiance, Hyderabad, Telangana 500081, IN
- Business categories
- Advice
- Artificial Intelligence
- Artificial Intelligence (AI)
- Financial Services
- Information Technology
- Other recorded names
- 73 Strings
- Specialties
- Venture Capital
- Private Equity
- SAAS
- Artificial Intelligence
- Banks
- Valuation
- Deal Sourcing
- Asset Management
- Data Science
- FASTech
- Private Debt
- Private Capital
- Growth Capital
- Private Assets
- Data Collection
- Risk
- Simulation
- Alternative Investment Funds
- and PETech
- Profile identifies a recruitment agency
- No
- Reported total investment
- 65,137,909
Currency and observation date were not supplied; this is not a current valuation or a funding round.
73 Strings is an award-winning agentic AI company transforming private capital operations through intelligent data extraction, portfolio monitoring, and valuation automation. Its AI-powered platform unifies fragmented investment workflows in a secure environment, enabling investment professionals to access trusted insights, automate processes, and make faster decisions. Trusted by 9 of the 10 global alternative…
| Field | Value |
|---|---|
| Industry | Financial Services |
| Company size | 201-500 employees |
| Headquarters | New York, NY |
| Organization type | Privately Held |
| Year founded | 2019 |
| Specialties | Venture CapitalPrivate EquitySAASArtificial IntelligenceBanksValuationDeal SourcingAsset ManagementData ScienceFASTech |
| Open jobs on Jobsy | 1 |
| View page |
OVERVIEW OF 73 STRINGS:
73 Strings is an innovative platform providing comprehensive data extraction, monitoring, and valuation solutions for the private capital industry. The company's AI-powered platform streamlines middle-office processes for alternative investments, enabling seamless data structuring and standardization, monitoring, and fair value estimation aAbout the role
We are hiring a Senior Data Engineer to build and operate the pipelines, integrations and warehouse that support valuation and monitoring.
You will own production pipelines from source capture through transformation, reconciliation and client delivery, and put them under GitHub, automated test and CI/CD. The platform currently captures change data from relational systems, processes it on Azure Databricks, and delivers it to Snowflake, Microsoft SQL Server and Databricks. The capture method may change. Copied client pipelines are being replaced by metadata-driven components, with data contracts, quality rules and lineage.
What you will do
Help redefine the platform’s architecture across ingestion, processing and delivery, so it’s stable, secure and fast enough to support advanced use cases for the business.
Build and operate batch and streaming pipelines from databases, APIs, event streams and semi-structured sources.
Implement change data capture and incremental load, including ordering, deletes, replay and slowly changing dimensions.
Build medallion datasets and dimensional models, and deliver them to Snowflake, Microsoft SQL Server and Databricks.
Apply data contracts, reconciliation and row-level quarantine before publication.
Own the GitHub workflow and CI/CD, including tests, review, environment promotion and deployment as code.
Investigate production data failures, and turn 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 the Snowflake equivalents: Dynamic Tables, Streams and Tasks, Snowpark, Snowflake CLI deployments and Data Metric Functions.
Debezium, Kafka Connect or Confluent Kafka. This is the current ingestion path. It may be replaced.
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.t the click of a button. 73 Strings serves clients globally across various strategies, including Private Equity, Growth Equity, Venture Capital, Infrastructure and Private Credit.
Our 2025 $55M Series B, the largest in the industry, was led by Goldman Sachs, with participation from Golub Capital and Hamilton Lane, with continued support from Blackstone, Fidelity International Strategic Ventures and Broadhaven Ventures.
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