Senior Data Engineer

Madison-Davis, LLC; United States; On-site; USD 200,000 - 225,000; Full time

Job summary

A leading company in staffing and recruiting seeks a Data Engineer to architect and maintain cloud-based data pipelines. The role requires extensive experience in data engineering, particularly in financial datasets, and offers a competitive salary range. The ideal candidate will apply DevOps principles and ensure data quality across various platforms.

Qualifications

• 10+ years in data engineering and architecture.
• 5+ years in Microsoft cloud environment.
• Experience with financial datasets.

Responsibilities

• Architect and maintain cloud-based data pipelines.
• Develop modular code for data transformations.
• Implement quality control and validation layers.

Skills

Data engineering

Cloud-native tooling

DevOps principles

Data governance

Investment concepts

Job description

This range is provided by Madison-Davis, LLC. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$200,000.00/yr - $225,000.00/yr

Role:

• Architect, engineer, build, and maintain cloud-based pipelines to handle critical financial datasets across multiple maturity zones—from raw ingestion to refined outputs.
• Develop modular code to support transformations, enrichment, and distribution across analytical and reporting layers.
• Apply DevOps principles to ensure scalable CI/CD for data flows and model deployments.
• Implement rigorous quality control via automated testing, validation layers, and documentation of logic/data lineage.
• Optimize data storage, access patterns, and architecture using a combination of structured and unstructured stores within a cloud-native data lakehouse environment.
• Design models and schemas that support cross-functional reporting and insights for business and technical users.
• Work closely with domain experts to bridge business needs and technical execution—particularly in the investment and reference data space.
• Support a federated model of data governance and help evangelize architecture best practices across global teams.
• Strong experience working with ingestion, processing, and transformation of external financial datasets (index, reference, benchmarks, third-party vendor feeds).
• Build robust orchestration pipelines using modern tooling, designed for auditability, version control, and scalability.
• Implement robust validation and reconciliation steps to ensure trust in critical reporting metrics (performance, AUM, benchmarks, etc.).
• Partner with business teams to design models that align with key investment concepts (portfolio structures, attribution, ESG, alternatives, etc.).
• Select optimal storage strategies depending on latency and volume needs—leveraging cloud-native compute and storage for performance at scale.
• Collaborate with analytics, reporting, and data science teams to deliver usable, trusted, and timely data products.
• 10+ years in data engineering and architecture, with a focus on cloud-native tooling and modern data platforms.
• 5+ years of recent experience building data solutions in a Microsoft cloud environment (ADFS, Delta-style frameworks, cloud data lake, etc.).
• Proven track record working in investment data domains (performance, attribution, ESG, etc.).
• Strong grasp of investment concepts and data structures tied to portfolio analytics, benchmarks, pricing, and security master data.
• Hands-on experience with modern data governance practices, pipeline observability, and enterprise data lifecycle management.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Staffing and Recruiting

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