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Weekend Data Engineering Jobs (NOW HIRING)

Peloton

Data Engineering Manager

New York, NY · On-site +1

ABOUT THE ROLE Peloton is looking for a talented Data Engineering Manager to join the Data Engineering team. In this role, you will lead the DataOps function, driving operational excellence across ...

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Daikin Comfort

Data Engineering Manager

Waller, TX · On-site

Daikin Comfort is seeking a Data Engineering Manager responsible for overseeing the design, development, and maintenance of data systems that support business intelligence and analytics initiatives.

Peloton

Data Engineering Manager

New York, NY · On-site

$173K - $213K/yr

ABOUT THE ROLE Peloton is looking for a talented Data Engineering Manager to join the Data Engineering team. In this role, you will lead the DataOps function, driving operational excellence across ...

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How much do weekend data engineering jobs pay per year?

As of Jul 10, 2026, the average yearly pay for weekend data engineering in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $300,000 or more annually. High compensation often reflects leadership roles, specialized knowledge, and working in competitive industries or organizations with high data demands.

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires expertise in cloud platforms, distributed systems, and leadership roles.

Do data engineers work on weekends?

Data engineers typically work regular business hours during weekdays, but they may work on weekends if project deadlines, system maintenance, or incident responses require it. Flexibility and availability during off-hours can be important, especially in environments with 24/7 data operations or real-time data processing needs.

What is the difference between Weekend Data Engineering vs Weekend Data Analysis?

AspectWeekend Data EngineeringWeekend Data Analysis
Required SkillsData pipeline development, SQL, Python, cloud platformsData interpretation, visualization, SQL, Excel
Work EnvironmentTechnical teams, data infrastructure projectsBusiness teams, reporting and insights
CertificationsData engineering certifications (e.g., Google Cloud, AWS)Data analysis certifications (e.g., Microsoft, Tableau)

Weekend Data Engineering focuses on building and maintaining data pipelines and infrastructure, requiring technical skills and cloud platform knowledge. In contrast, Weekend Data Analysis emphasizes interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but serve different functions during weekend projects or part-time work.

What jobs make $1,000,000 a year?

High-level executive roles such as CEOs, CFOs, and other C-suite positions can earn over $1 million annually, often including bonuses and stock options. Certain specialized professions like top-tier investment bankers, hedge fund managers, and successful entrepreneurs also reach this income level, typically requiring extensive experience, advanced skills, and significant responsibility.
What cities are hiring for Weekend Data Engineering jobs? Cities with the most Weekend Data Engineering job openings:
What are the most commonly searched types of Data Engineering jobs? The most popular types of Data Engineering jobs are:
What states have the most Weekend Data Engineering jobs? States with the most job openings for Weekend Data Engineering jobs include:
Weekend Data Engineering jobs near you
Data Engineering Manager

Data Engineering Manager

Bollinger Shipyards

Raceland, LA • On-site

Full-time

Re-posted 23 days ago

Bollinger Shipyards rating

5.5

Company rating: 5.5 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

Job description

Job Title: Data Engineering Manager
Location: Multiple Location
Position Overview: The Data Engineering Manager leads the design, development, and delivery of enterprise data pipelines and foundational data assets supporting analytics, reporting, forecasting, and AI initiatives. This role is responsible for establishing scalable and reliable data engineering practices while ensuring enterprise data is accurate, secure, accessible, and aligned to business priorities.
The role partners closely with Enterprise Architecture, Analytics, Data Science, Infrastructure, and business stakeholders to integrate data from ERP, operational, engineering, and manufacturing systems into the enterprise Azure data platform.
Key Responsibilities:
• Lead the development and support of enterprise data pipelines and integrations across Oracle ERP, Finesse, MES, PLM, Primavera, proposal systems, and other operational platforms
• Establish and maintain scalable data engineering standards, frameworks, and development practices
• Ensure consistent implementation of enterprise data architecture and medallion data design patterns (raw, curated, business-ready)
• Oversee data ingestion, transformation, orchestration, reconciliation, and validation processes
• Partner with Enterprise Architecture and Integration teams to align technical solutions with enterprise standards and future-state architecture
• Support analytics, reporting, forecasting, and AI initiatives through delivery of trusted and performant datasets
• Ensure data quality, lineage, observability, and reliability across enterprise data assets
• Manage priorities, sprint planning, delivery timelines, and technical execution for the data engineering team
• Collaborate with cybersecurity and infrastructure teams to ensure secure and compliant handling of enterprise data
• Evaluate emerging technologies and recommend improvements to data engineering capabilities and platform performance
• Mentor and develop technical talent while fostering strong engineering discipline and accountability
Qualifications:
• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, or related field
• 8-12 years of experience in data engineering
• Proven experience delivering enterprise-scale data pipelines
• Strong SQL and data transformation expertise
• Experience with cloud data platforms (Azure preferred)
• Experience integrating ERP and operational systems
Skills and Abilities:
• Experience with Azure Synapse, Azure Data Factory, Databricks, Fabric, or similar cloud technologies
• Experience in manufacturing, shipbuilding, industrial, or engineering-intensive environments
• Familiarity with Power BI and downstream analytics enablement
• Experience supporting AI/ML initiatives through engineered datasets and feature pipelines
• Knowledge of data observability, master data management, and metadata management practices
• Relevant cloud or data engineering certifications
Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity.

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