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Find Data Jobs (NOW HIRING)

Wisconsin

Data Scientist II

Madison, WI · On-site +1

$80K/yr

Independently identifies and implements appropriate data science techniques to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical ...

Apple

Senior Data Engineer, Find My

Cupertino, CA · On-site

$130.80K - $177.70K/yr

We embrace continuous iteration and improvement, so you'll have the opportunity to learn, grow, and refine your skills as we build the future of Find My.You will translate analytics needs from Data ...

Apple

Senior Data Engineer, Find My

Cupertino, CA

$181.10K - $318.40K/yr

We embrace continuous iteration and improvement, so you'll have the opportunity to learn, grow, and refine your skills as we build the future of Find My. You will translate analytics needs from Data ...

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$46K

$165K

$243.5K

How much do find data jobs pay per year?

As of May 30, 2026, the average yearly pay for find data in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Find Data vs Data Analyst?

AspectFind DataData Analyst
Required CredentialsTypically requires a basic understanding of data collection and analysis tools, often with a degree in a related fieldUsually requires a degree in statistics, mathematics, or related fields, with certifications in data analysis tools
Work EnvironmentOften involves data gathering, research, and preliminary analysis, working in research or data collection settingsFocuses on interpreting data, creating reports, and providing insights, working in business or corporate environments
Employer & Industry UsageUsed in research firms, data collection agencies, and initial data gathering rolesEmployed across industries like finance, marketing, healthcare, and technology for data-driven decision making

Find Data primarily involves collecting and preparing data for analysis, while Data Analysts interpret and analyze data to generate insights. Both roles are essential in data workflows but differ in focus and skill requirements.

More about Find Data jobs
What cities are hiring for Find Data jobs? Cities with the most Find Data job openings:
What states have the most Find Data jobs? States with the most job openings for Find Data jobs include:
What job categories do people searching Find Data jobs look for? The top searched job categories for Find Data jobs are:
Find Data jobs near you
Infographic showing various Find Data job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 72% Full Time, 20% Part Time, and 6% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Senior Data Engineer (Azure & Databricks)

Senior Data Engineer (Azure & Databricks)

Emergent Software

Bloomington, MN • On-site

$60 - $85/hr

Contractor

Posted 25 days ago

Job description

** This is a 6+ month contract with our client based out of Bloomington, MN. This is a hybrid role, working in office Tuesday/Thursday. Candidates must be able to work in the US without sponsorship.**
We're looking for a Senior Data Engineer with strong Azure experience, especially in Azure Databricks, Delta Lake, and SQL, to build and scale a medallion-based data platform. This role focuses on designing high-performance, governed data pipelines using PySpark, SQL, and Databricks tools to integrate data from Azure systems, SQL Server Managed Instance, and third-party sources, while partnering closely with analytics teams and business stakeholders. Experience or strong interest in supporting AI/ML use cases is highly valued, with financial-services experience considered a plus but not required.
Responsibilities
  • Design, develop, and optimize data pipelines in Azure Databricks using PySpark and SQL, applying Delta Lake and Unity Catalog best practices.
  • Build modular, reusable libraries and utilities within Databricks to accelerate development and standardize workflows.
  • Implement Medallion architecture (Bronze, Silver, Gold layers) for scalable, governed data zones.
  • Integrate external data sources via REST APIs, SFTP file delivery, and SQL Server Managed Instance, implementing validation, logging, and schema enforcement.
  • Utilize parameter-driven jobs and manage compute using Spark clusters and Databricks serverless.
  • Collaborate with data analytics teams and business stakeholders to understand requirements and deliver analytics-ready datasets.
  • Monitor and troubleshoot Azure Data Factory (ADF) pipelines (jobs, triggers, activities, data flows) to identify and resolve job failures and data issues.
  • Automate deployments and manage code using Azure DevOps for CI/CD, version control, and environment management.
  • Contribute to documentation, architectural design, and continuous improvement of data engineering best practices.
  • Support the design and readiness of the data platform for AI and machine learning initiatives.
Requirements
  • Strong expertise with Azure Databricks, including PySpark, Delta Lake, Unity Catalog, and the ability to build reusable libraries, utility notebooks, and parameterized jobs.
  • Advanced SQL skills with experience working in Azure SQL Database and/or SQL Server Managed Instance.
  • Experience designing, troubleshooting, and supporting data pipelines using Azure Data Factory.
  • Proven ability to integrate external data sources, including REST APIs and SFTP.
  • Working knowledge of Azure DevOps for CI/CD, version control, and parameterized deployments.
  • Demonstrated experience partnering closely with data analytics teams and business stakeholders, supported by strong communication, problem-solving, and collaboration skills.
  • Interest or experience in preparing data platforms to support AI and machine learning initiatives.
Nice to Haves
  • Experience implementing Medallion architecture within governed Azure data environments, including data governance and RBAC.
  • Familiarity with data warehousing concepts, dimensional modeling, and preparing datasets for BI tools such as Power BI.
  • Understanding of Spark performance optimization, cluster or serverless compute management, and advanced Delta Lake features.
  • Hands-on experience preparing datasets to support AI/ML use cases.
  • Prior experience in the financial-services industry.
Our Vetting Process
At Emergent Staffing, we work hard to find Data Engineers who are the right fit for our clients. Here are the steps of our vetting process for this position:
  • Application (5 minutes)
  • Online Assessment (40 minutes)
  • Initial Phone Interview (30-45 minutes)
  • Virtual Interview with Hiring team
  • Onsite Interview
  • Job Offer!

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