RRole- Senior Data Engineer (Snowflake / Python / Financial Services) – United States

Location- Remote

Experience Required – 10+Years

Employment Type –Contract

Industry Preference – Asset Management / Capital Markets / Financial Services


Job Summary

We are seeking two highly experienced Senior Data Engineers to design, build, and scale a modern investments data platform. The ideal candidates will have strong expertise in Snowflake, SQL, Python, and modern ELT frameworks, along with experience handling complex financial datasets.

This is a hands-on role in a lean, high-impact engineering team where you will help shape the architecture, development standards, and long-term scalability of the investment data platform.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and data platforms.
  • Build and optimize data solutions using Snowflake.
  • Develop ELT workflows using modern frameworks such as dbt, Airflow, or similar tools.
  • Write efficient and complex SQL queries for large-scale financial datasets.
  • Develop Python-based data processing and automation scripts.
  • Design and implement robust data models to support investment and financial analytics.

Required Skills and Qualifications

  • 10–15 years of experience in data engineering.
  • Strong hands-on experience with Snowflake.
  • Advanced SQL skills.
  • Proficiency in Python for data engineering and automation.
  • Experience with modern ELT frameworks (dbt, Airflow, Matillion, or similar).
  • Strong understanding of dimensional modeling and data warehousing concepts.
  • Experience designing data models for complex financial datasets.
  • Knowledge of data governance, lineage, and quality controls.
  • Experience building scalable and maintainable data architectures.

Nice-to-Have Skills

  • Experience with cloud platforms (AWS, Azure, or GCP).
  • Knowledge of orchestration and workflow scheduling tools.
  • Familiarity with DevOps, CI/CD, and infrastructure-as-code.
  • Experience with market, portfolio, performance, and risk data.
  • Exposure to data cataloging and metadata management tools.

 

 

 

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