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Flex Schedule Meta Data Analyst Jobs (NOW HIRING)

Data Analyst

Clark, NJ ยท On-site

... meta-data, data lineage, data cleansing services *Activities: data modeling, data audit, detailed ... Analytical *Self-starter *Proficient in English (written & oral) *Critical Thinking *Employ ...

A career at Flex offers the opportunity to make a difference and invest in your growth in a ... Typically, then, a data analyst will want to have at least 1-2 years experience in a specific field ...

Data Analyst

Austin, TX ยท On-site

A career at Flex offers the opportunity to make a difference and invest in your growth in a ... Same as grade 23. Typically, then, a data analyst will want to have at least 2-4 years of ...

Meta is seeking an experienced Logistics Operations Specialist to focus on Data Center Field and ... Support the execution of Sarbanes-Oxley requirements, analyze discrepancies and assist teams to ...

Develops queries, reports, dashboards and processes to continuously monitor data/meta data quality ... Performs root case analysis on data and identifies approaches to resolve. * Performs complex data ...

This role is at the heart of Meta's mission to build technologies that bring the world closer ... Lead infrastructure system engineering changes by defining project scope, schedule, and priority ...

Meta is seeking an experienced Logistics Operations Specialist to focus on Data Center Field and ... Support the execution of Sarbanes-Oxley requirements, analyze discrepancies and assist teams to ...

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Flex Schedule Meta Data Analyst information

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$34K

$82.6K

$136K

How much do flex schedule meta data analyst jobs pay per year?

As of Jun 23, 2026, the average yearly pay for flex schedule meta data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

Is a data analyst still worth it in 2026?

A data analyst, including roles like Flex Schedule Meta Data Analyst, remains valuable in 2026 as organizations continue to rely on data-driven decision making. Skills in SQL, Excel, and data visualization tools are essential, and remote or flexible schedules are increasingly common, supporting ongoing demand for these professionals.

What is the difference between Flex Schedule Meta Data Analyst vs Data Analyst?

AspectFlex Schedule Meta Data AnalystData Analyst
CredentialsBachelor's in Data Science, Statistics, or related field; familiarity with data toolsBachelor's in similar fields; proficiency in data analysis software
Work EnvironmentFlexible hours, remote or hybrid options, project-based tasksStandard office hours, on-site or remote roles, ongoing data projects
Industry UsageTech, finance, healthcare with flexible scheduling needsBroad industry application, often with fixed schedules

The Flex Schedule Meta Data Analyst typically offers flexible working hours and focuses on managing and analyzing data with adaptable schedules. In contrast, a Data Analyst often works standard hours in a more structured environment. Both roles require similar skills and educational backgrounds but differ mainly in work hours and flexibility.

How flexible are data analyst jobs?

Data analyst jobs, including those with flexible schedules, often offer options such as remote work, part-time hours, or flexible start and end times. The level of flexibility depends on the employer, company policies, and the specific role, with many organizations increasingly adopting adaptable work arrangements to attract talent.

How much does Meta pay data analysts?

Meta data analysts typically earn an average salary ranging from $70,000 to $120,000 annually, depending on experience, location, and level within the company. Compensation may also include bonuses, stock options, and benefits, with roles often requiring proficiency in data analysis tools like SQL and Python. Entry-level positions tend to start at the lower end of this range, while experienced analysts can earn higher salaries.

Is 40 too late for data science?

For a Flex Schedule Meta Data Analyst or similar data science roles, starting a career at age 40 is feasible, as many employers value skills and experience over age. Success depends on your technical skills, such as proficiency in SQL, Python, or R, and your ability to learn new tools. Continuous learning and relevant certifications can enhance your prospects regardless of age.
More about Flex Schedule Meta Data Analyst jobs
What cities are hiring for Flex Schedule Meta Data Analyst jobs? Cities with the most Flex Schedule Meta Data Analyst job openings:
What states have the most Flex Schedule Meta Data Analyst jobs? States with the most job openings for Flex Schedule Meta Data Analyst jobs include:
Infographic showing various Flex Schedule Meta Data Analyst job openings in the United States as of June 2026, with employment types broken down into 3% As Needed, 89% Part Time, and 8% Contract. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.
Sr. Data Analyst w/Pharma OR Medical Devices Exp

Sr. Data Analyst w/Pharma OR Medical Devices Exp

Palnar

Princeton, NJ โ€ข On-site

$90K - $113K/yr

Full-time

Posted 19 days ago


Job description

Required Skills - Strong Data Analysis, Strong Meta Data, Strong SQL/Python, Pharmaceuticals or Medical Devices experience is a must.
Cloud Experience is Desired.
The role of the data analyst involves collaborating with the data product owner, curating metadata, setting up information for the marketplace, and transforming assets into data products. This includes defining the purpose of each Data Product and understanding its usage.
The candidate will play a supporting role in implementing the Data Marketplace. They should have a data product-oriented mindset, creating purpose-built Data Products by combining them strategically. For instance, if R&D requires ten data sets for a specific purpose, Data Product Owners define and structure the data products accordingly.
Despite having 15 Data Product Owners overseeing various data products, there is a need for someone who can work hands-on. This individual should collaborate with different product owners and curate information for each of the 10 data products, focusing on generating business metadata. The emphasis is on practical, hands-on work rather than a strictly process-oriented approach.
The ideal candidate should be knowledgeable about AWS, specifically Datazone, as some work related to porting data onto the marketplace will commence. While this knowledge is beneficial, it's not a strict requirement.