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73 Strings

Senior Data Engineer

73 Strings · Municipality of Al Shamal, Riyadh Region, Saudi Arabia

Financial Services · 201-500 employees

2 d ago
Principal (10+ yrs) Full-time Saudi Arabia
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About the role

Lead the enterprise data architecture strategy, focusing on scalability, governance, and the implementation of cloud data warehousing solutions. Act as a technical advisor for strategic clients and design robust API and data integration patterns.

What they look for

Data Architecture Snowflake Databricks REST APIs ETL/ELT Pipelines Kafka Flink Spark dbt Apache Airflow AWS Azure GCP Vector Databases LLM RAG Architectures

Requirements

Requires 8+ years of experience in data architecture with deep expertise in Snowflake, Databricks, and real-time streaming platforms. Must have hands-on experience with LLM/RAG architectures and integrating unstructured data into structured platforms.

Full description

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 at 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.

About the Role:

We are seeking a Senior Data Architect to serve as a technical lead shaping the future of our data platform in the financial services space. This is a high-impact, hands-on leadership role — you will own architectural direction, drive integration strategy, and act as a trusted technical advisor to both internal stakeholders and external clients.

What You’ll Do

Data Platform Leadership

  • Define and evolve the enterprise data architecture strategy, ensuring scalability, reliability, and governance across the platform.
  • Lead the design and implementation of cloud data warehousing and lakehouse solutions, with a focus on Snowflake and Databricks, aligned with financial services data requirements.
  • Establish data modeling standards, data quality frameworks, and best practices across engineering teams.
  • Champion data governance, security, and compliance practices in alignment with financial industry regulations (e.g., SOC 2, GDPR, CCPA).

Integrations & API Development

  • Partner with Product Management and business stakeholders to design and deliver robust data integrations and APIs (REST, GraphQL, ETL/ELT pipelines).
  • Architect scalable, reusable integration patterns that connect internal systems, third-party platforms, and client data ecosystems.
  • Define API contracts, data schemas, and integration standards that support both internal development teams and external partners.
  • Translate complex business and regulatory requirements into sound, implementable technical designs.

Client Engagement & Technical Advisory

  • Act as the primary technical point of contact for strategic clients and prospects, building trusted relationships with their senior engineering, data, and technology leadership.
  • Lead client-facing architectural discussions, workshops, and design sessions to understand data challenges and present credible, tailored solutions.
  • Support pre-sales and implementation teams by providing architectural guidance, responding to technical due diligence requests, and contributing to RFPs and solution proposals.
  • Translate client business and regulatory requirements into clear, implementable technical designs — communicating confidently across both executive and engineering audiences.

Requirements:

  • 8+ years of experience in data architecture or data engineering.
  • Proven expertise in cloud data platforms such as Snowflake, Databricks, including data modeling, performance tuning, and cost optimization.
  • Hands-on experience designing and building REST APIs and ETL/ELT pipelines at scale.
  • Strong proficiency with real-time and streaming data platforms such as Kafka, Flink, and Spark.
  • Hands-on experience with modern data orchestration and transformation tools such as dbt and Apache Airflow.
  • Experience with data testing frameworks, pipeline observability, and monitoring practices that ensure data quality, reliability, and operational visibility in production environments.
  • Experience with major cloud platforms (AWS, Azure, or GCP), including cloud-native data services, networking, and security.
  • Proven experience with vector database or embedding infrastructure in production.
  • Experience integrating unstructured data (documents, PDFs, presentations) into a structured data platform, including extraction, normalisation, and lineage back to source artefacts.
  • Demonstrated ability to drive technical strategy and lead cross-functional projects.
  • Working understanding of LLM and RAG architectures, including tenant-aware retrieval, context isolation, and the data quality and lineage prerequisites for safe deployment.
  • Strong communication skills with the ability to translate complex technical concepts for executive and non-technical audiences.