Enterprise Data Architect

Harvey Nash; United States; Hybrid; USD 180,000 - 250,000; Full time

Job summary

A leading consulting firm is looking for a skilled Cloud Data Architect with expertise in Snowflake and Databricks. This role involves leading a team to design cloud-native data platforms, focusing on the financial services sector. Candidates should have over 10 years of experience in data engineering, strong technical leadership skills, and knowledge of cloud platforms. This full-time position allows for remote work, requiring limited onsite travel. Excellent communication skills are essential for this role.

Qualifications

• 10–12+ years of data engineering/data architecture experience, including 3+ years in technical leadership.
• Expertise in Snowflake, Databricks, or both.
• Experience architecting large-scale, cloud-native data platforms.
• Proven experience architecting large-scale cloud-native data platforms.

Responsibilities

• Define enterprise-level cloud data architecture emphasizing Snowflake or Databricks.
• Lead data centralization strategies across workloads.
• Provide thought leadership on cloud modernization and governance.
• Build, optimize, and oversee ETL/ELT pipelines.

Skills

Snowflake

Databricks

Python

SQL

Spark

Kafka

MLOps

AI-ready architectures

Tools

AWS

Azure

GCP

Scala

Java

Job description

This range is provided by Harvey Nash. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$180,000.00/yr - $250,000.00/yr

Job Title: Cloud Data Architect (Snowflake / Databricks)

Location: Remote with limited monthly onsite travel (expenses covered)

Duration: Contract, Contract-to-Hire, or Full-Time Permanent

US Citizens, Green Card Holders, and all authorized to work in the U.S. are encouraged to apply.

Summary

We are seeking a highly skilled Cloud Data Architect with deep hands‑on experience in Snowflake or Databricks, modern data engineering practices, and advanced cloud capabilities (AWS, Azure, or GCP). The ideal candidate has a strong background supporting Banking, Investment, Financial Services, Insurance, or Payment industry data platforms, including secure, scalable, and compliant architectures.

This position blends 60–70% strategic architecture with 30–40% hands‑on engineering. Candidates with exposure to AI/ML platforms, MLOps, or AI‑ready data infrastructures are strongly preferred.

A future security clearance may be required for select projects.

Role Overview

As a Principal Cloud Data Architect, you will lead a team of five and drive end‑to‑end architecture and delivery for a key enterprise data modernization initiative. You will work closely with cross‑functional business and technology stakeholders to design and deliver resilient, high‑performance, cloud‑native data platforms.

Industry experience in Banking, Payments, FinTech, Capital Markets, or Insurance is highly desirable due to the regulatory, compliance, and data governance complexities of this environment.

Key Responsibilities

• Define and drive enterprise‑level cloud data architecture, with an emphasis on Snowflake or Databricks.
• Lead data centralization strategies across transactional, analytical, and real‑time workloads.
• Architect secure, scalable, compliant data ecosystems aligned to BFSI (Banking, Financial Services, Insurance) standards.
• Provide thought leadership across cloud modernization, data mesh, AI enablement, and governance frameworks.
• Build, optimize, and oversee ETL/ELT pipelines using Spark, Databricks, dbt, or Snowflake‑native capabilities.
• Implement data integration APIs and real‑time streaming frameworks (Kafka, Kinesis, Event Hub).
• Develop and maintain cloud data warehousing solutions (Snowflake, Databricks Lakehouse).
• Lead a high‑performing engineering team through project and delivery cycles.
• Partner with both technical and non‑technical stakeholders to translate business needs into scalable data solutions.
• Promote best practices in system design, cloud architecture, and secure data engineering.

Required Skills & Experience

• 10–12+ years of data engineering / data architecture experience, including 3+ years in technical leadership.
• Strong expertise in Snowflake, Databricks, or both.
• Proven experience architecting large‑scale, real‑time, cloud‑native data platforms in regulated industries.
• Mastery of distributed data processing systems and real‑time analytics (Spark, Kafka, Flink).
• Advanced proficiency in Python, SQL, and preferably Scala or Java.
• Deep knowledge of AWS, Azure, or GCP for data storage, compute, security, and analytics services.
• Experience launching data‑driven financial products, data platforms, or digital services at scale.
• Strong understanding of GenAI, AI‑ready architectures, and MLOps practices.
• Excellent communication and leadership skills, with the ability to drive technical excellence and innovation.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering, Information Technology, and Other

Industries

Banking, Insurance, and Financial Services

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