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Weekend Financial Data Engineer Jobs (NOW HIRING)

Incedo Inc

Data Engineer

Austin, TX

$113K - $136K/yr

This role sits at the intersection of financial data and modern cloud engineering you will design, build, and maintain the data pipelines and infrastructure that power our advisor and client ...

Self Financial

Staff Data Engineer

Austin, TX

$160K - $195K/yr

As part of the Self Financial Data Engineering Team, your role will be to ensure that data remains a strategic asset for Self Financial by delivering timely, high-quality, and purpose-built data to ...

dBestWorkz LLC

Senior Data Engineer

Phoenix, AZ

$105K - $143K/yr

The Senior Data Engineer will be responsible for analyzing financial data processing workflows and translating business requirements into scalable technical data solutions. They will work closely ...

New

IT America Inc

Data Engineer

Mclean, VA · On-site

$115K - $139K/yr

Data Engineer Location: Mclean, VA Duration: Long term contract Note: Looking for Ex-Capital One ... financial data. This role involves working closely with Capital One's data, analytics, and ...

VTG

Senior Data Engineer

Chantilly, VA · On-site

$109K - $148K/yr

In this dynamic role, you will not only support the team in conditioning financial data but also play a key role in the adoption of modern data engineering practices. Your contributions will directly ...

VTG

Senior Data Engineer

Herndon, VA · On-site

$109K - $148K/yr

In this dynamic role, you will not only support the team in conditioning financial data but also play a key role in the adoption of modern data engineering practices. Your contributions will directly ...

Apple

Data Engineer, Operations Finance

Sunnyvale, CA

$146K - $244K/yr

Collaborate with financial analysts, engineers, and operations experts to understand data needs and translate them into scalable data foundational structures. Build scalable, flexible, and high ...

VTG

Senior Data Engineer

Chantilly, VA

$109K - $148K/yr

In this dynamic role, you will not only support the team in conditioning financial data but also play a key role in the adoption of modern data engineering practices. Your contributions will directly ...

Guidehouse

Data Engineer

Mclean, VA · On-site

$85K - $141K/yr

Partner with functional SMEs, financial analysts, platform engineers, and governance teams to ensure data pipelines conform to DoD financial data standards, business rules, and controls. * Implement ...

KORE1 Technologies

Data Engineer

Charleston, SC · On-site

$160K/yr

The Data Engineer will own the end-to-end data stack, including ingestion, transformation, modeling ... Design and implement canonical data models across financial and operational datasets. * Write and ...

KORE1 Technologies

Data Engineer

Charleston, SC · On-site +1

$107K - $128K/yr

The Data Engineer will own the end-to-end data stack, including ingestion, transformation, modeling ... Design and implement canonical data models across financial and operational datasets. * Write and ...

Apple

Finance Data Engineer

Austin, TX · On-site

$113K - $136K/yr

The Finance Data Engineer is a technical expert who creates data interfaces, pipelines and codebase that drives innovative data products for Apple Finance. They build reliable, accurate, consistent ...

Apple

Finance Data Engineer

Austin, TX · On-site

$113K - $136K/yr

The Finance Data Engineer is a technical expert who creates data interfaces, pipelines and codebase that drives innovative data products for Apple Finance. They build reliable, accurate, consistent ...

Career Renew

Data Engineer

Boston, MA · Hybrid

$150K - $250K/yr

We equip Finance Teams at complex, sophisticated businesses to drive strategic decisions by ... About this role We are looking for a Data Engineer with ideally 3+ years of experience to design ...

Cypress HCM

Data Engineer 3

San Jose, CA · Hybrid

$65.49/hr

The Financial Data Engineer performs a wide range of job duties utilizing technical know-how and develop an analytics product that will generate insights into financial metrics and customer journey.

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All JobsWeekend Financial Data Engineer Jobs

Weekend Financial Data Engineer information

See salary details

$60.5K

$122.1K

$167.5K

How much do weekend financial data engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for weekend financial data engineer in the United States is $122,112.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,500.00 and $140,000.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Financial Data Engineer vs Weekend Financial Data Analyst?

AspectWeekend Financial Data EngineerWeekend Financial Data Analyst
Required CredentialsBachelor's in Computer Science, Finance, or related field; experience with data engineering toolsBachelor's in Finance, Economics, or related; strong analytical skills
Work EnvironmentFocus on building data pipelines, managing databases, and infrastructureFocus on analyzing data, creating reports, and providing insights
Employer & Industry UsageFinancial institutions, fintech companies, investment firmsBanking, investment firms, financial consultancies
Common Search & ComparisonOften compared based on technical skills and infrastructure tasksCompared based on analytical skills and reporting capabilities

The Weekend Financial Data Engineer primarily focuses on developing and maintaining data infrastructure, requiring technical skills in data engineering tools. In contrast, the Weekend Financial Data Analyst emphasizes analyzing financial data and generating insights. Both roles are vital in financial organizations but differ in their core responsibilities and skill sets.

More about Weekend Financial Data Engineer jobs
What cities are hiring for Weekend Financial Data Engineer jobs? Cities with the most Weekend Financial Data Engineer job openings:
What are the most commonly searched types of Financial Data Engineer jobs? The most popular types of Financial Data Engineer jobs are:
What states have the most Weekend Financial Data Engineer jobs? States with the most job openings for Weekend Financial Data Engineer jobs include:
What job categories do people searching Weekend Financial Data Engineer jobs look for? The top searched job categories for Weekend Financial Data Engineer jobs are:
Weekend Financial Data Engineer jobs near you
Infographic showing various Weekend Financial Data Engineer job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $122,112 per year, or $58.7 per hour.
Data Engineer

Data Engineer

Incedo Inc

Austin, TX

$113K - $136K/yr

Other

Posted 23 days ago

Job description

Data Engineer Wealth Management Platform

Employment Type: Full-Time

About the Role

We are seeking a skilled Data Engineer with a strong wealth management background to join our data and technology team. This role sits at the intersection of financial data and modern cloud engineering you will design, build, and maintain the data pipelines and infrastructure that power our advisor and client reporting, reconciliation processes, and platform integrations.

The ideal candidate brings hands-on experience with Databricks and the Microsoft cloud ecosystem, a deep understanding of wealth management data domains, and the ability to leverage AI tooling to accelerate their daily work.

Key Responsibilities

Data Pipeline Development & Engineering

  • Design, build, and maintain scalable data pipelines using Databricks and Azure cloud services
  • Develop and optimize PySpark and Python-based ETL/ELT workflows for ingesting, transforming, and serving wealth management data
  • Build and manage data models that support advisor, account, client, position, transaction, and security datasets
  • Ensure data pipelines meet performance, reliability, and latency requirements for downstream consumers

Financial Data & Reconciliation

  • Reconcile financial datasets across custodians, internal systems, and third-party data providers identifying and resolving breaks at the position, transaction, and account level
  • Partner with operations and service teams to investigate and resolve data discrepancies impacting advisors and clients
  • Implement data quality checks, validation rules, and alerting to proactively catch data integrity issues
  • Support the build-out of reconciliation frameworks that scale across growing data volumes and entity counts

Cloud Infrastructure & Platform

  • Build and manage data infrastructure on Microsoft Azure, including Azure Data Factory, Azure Data Lake, and related services
  • Contribute to the architecture and governance of the data lakehouse environment within Databricks (Delta Lake, Unity Catalog)
  • Collaborate with platform and DevOps teams on CI/CD pipelines, environment management, and data infrastructure as code

AI-Augmented Engineering

  • Actively leverage AI coding assistants and automation tools (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate development, code review, and documentation
  • Identify opportunities to apply AI/ML techniques to financial data problems such as anomaly detection, break prediction, or data classification
  • Stay current on emerging AI tooling and bring practical recommendations to the team
Required Qualifications
  • 5 8 years of experience in data engineering, with direct exposure to wealth management data domains
  • Databricks Certified (Associate or Professional) or demonstrated deep, hands-on Databricks expertise in a production environment
  • Proficiency in Python and PySpark for building and optimizing large-scale data pipelines
  • Hands-on experience with Microsoft Azure cloud services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse, or equivalent)
  • Direct experience working with wealth management data including positions, transactions, accounts, clients, advisors, and security master data
  • Experience reconciling financial datasets across custodians, platforms, or internal systems
  • Strong understanding of data modeling, ETL/ELT patterns, and data warehouse or lakehouse architecture
  • Demonstrated use of AI tools in day-to-day engineering work this is not optional; we expect engineers to be actively leveraging AI to move faster and work smarter

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