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Remote Data Transformation Analyst Jobs in Baltimore, MD

Under Armour

Sr. Data Analytics Engineer

Baltimore, MD · On-site +1

$125K - $165K/yr

Expert SQL abilities with mastery in complex data transformation patterns. * Deep expertise in data ... Location: Remote (East Coast strongly preferred to optimize collaboration with HQ and cross ...

Goldman Edwards, Inc.

Be Seen First

Budget Analyst (Remote)

Baltimore, MD · Remote

... data transformation, and visualization capabilities. · Experience with data visualization tools (e.g., Power BI, Tableau) for financial reporting. · Proficiency with Microsoft Excel and financial ...

New

Moore

Data Analyst

Lanham, MD · Remote

... and transformation. * Identify trends, patterns, and outliers in complex data sets to drive ... remote

New

Booz Allen Hamilton, Inc.

Data Engineer

Aberdeen, MD · On-site +1

$77K - $176K/yr

Remote Work: Yes Job Number: R0243265 Location: Belcamp,MD,US Share job via: Share Additional ... You'll use your experience in analytical exploration and data examination while you manage the ...

Booz Allen Hamilton, Inc.

Data Engineer

Aberdeen, MD · On-site +1

$77K - $176K/yr

Remote Work: Yes Job Number: R0241931 Location: Belcamp,MD,US Share job via: Share Additional ... You'll use your experience in analytical exploration and data examination while you manage the ...

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All JobsData Transformation Analyst JobsRemote Data Transformation Analyst JobsRemote Data Transformation Analyst Jobs in Baltimore, MD

Remote Data Transformation Analyst information

See Baltimore, MD salary details

$33.8K

$82.1K

$135.1K

How much do remote data transformation analyst jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote data transformation analyst in Baltimore, MD is $82,114.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,100.00 and $96,400.00 per year, depending on experience, location, and employer.

What are some common challenges faced by remote data transformation analysts and how can they be addressed?

Remote Data Transformation Analysts often encounter challenges such as ensuring data accuracy across multiple sources, collaborating effectively with geographically dispersed teams, and managing tight project deadlines. To address these, it's important to establish clear communication channels, use project management tools to track progress, and routinely validate data transformations to maintain quality. Proactively seeking feedback from team members and stakeholders can also help quickly identify and resolve any issues, fostering a more efficient and collaborative remote work environment.

What is a remote data transformation analyst?

A Remote Data Transformation Analyst is a professional who specializes in converting, cleaning, and organizing raw data into usable formats for analysis, all while working from a remote location. They work with large datasets, using tools and programming languages such as SQL, Python, or ETL (Extract, Transform, Load) platforms to ensure data accuracy and consistency. Their work supports business intelligence, reporting, and decision-making processes by making data accessible and actionable for stakeholders. Remote Data Transformation Analysts often collaborate with data engineers, data scientists, and other IT professionals to deliver high-quality data solutions.

What is the difference between Remote Data Transformation Analyst vs Remote Data Engineer?

AspectRemote Data Transformation AnalystRemote Data Engineer
Required CredentialsBachelor's in Data Science, IT, or related field; SQL, Excel, data visualization skillsBachelor's or higher in Computer Science, Data Engineering; SQL, Python, cloud platforms
Work EnvironmentRemote, often part-time or project-based, collaborating with analysts and business teamsRemote or hybrid, involved in building and maintaining data pipelines and infrastructure
Employer & Industry UsageBusiness intelligence firms, finance, healthcare, retailTech companies, finance, e-commerce, large enterprises

The Remote Data Transformation Analyst focuses on cleaning, transforming, and visualizing data to support decision-making, while the Remote Data Engineer designs and maintains the data infrastructure and pipelines. Both roles require SQL skills and often work remotely, but Data Engineers typically have more programming and infrastructure responsibilities.

What are the key skills and qualifications needed to thrive as a remote data transformation analyst, and why are they important?

To thrive as a Remote Data Transformation Analyst, you need strong analytical skills, proficiency in data manipulation, and a background in computer science, information systems, or a related field. Familiarity with ETL tools (like Talend or Informatica), SQL, and data visualization platforms, as well as certifications in data analytics or related areas, are typically required. Excellent attention to detail, problem-solving abilities, and effective remote communication skills help you stand out in this role. These skills ensure accurate data transformation, seamless collaboration across distributed teams, and the delivery of actionable insights for business decision-making.
What are popular job titles related to Remote Data Transformation Analyst jobs in Baltimore, MD? For Remote Data Transformation Analyst jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Remote Data Transformation Analyst jobs in Baltimore, MD look for? The top searched job categories for Remote Data Transformation Analyst jobs in Baltimore, MD are:
Remote Data Transformation Analyst jobs near you
Infographic showing various Remote Data Transformation Analyst job openings in Baltimore, MD as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $82,114 per year, or $39.5 per hour.

Data Engineer (Remote)

Magpie Health Analytics

Baltimore, MD • Remote

$117K - $140K/yr

Full-time

Posted 11 days ago

Job description

Position Purpose:

We are seeking a Data Engineer to support the development of cloud-native data solutions that improve operational efficiency, support regulatory reporting, and drive actionable insight for our commercial and government healthcare clients. This role is responsible for building, maintaining, and optimizing scalable data pipelines and validation workflows across complex datasetsenabling downstream analytics, application logic, and system modernization initiatives.

Primary Duties & Responsibilities:

  • Design, develop, and maintain ETL/ELT pipelines using structured and semi-structured data from relational databases, flat files, APIs, and cloud data sources.
  • Collaborate with backend and architecture teams to define data transformation flows aligned with dashboard and reporting application needs.
  • Design and optimize data schemas to ensure performance, integrity, and compatibility with reporting requirements.
  • Develop and maintain efficient, testable, and reusable data processing scripts using Python, SQL, and cloud-native tools.
  • Collaborate with DevOps, analysts, and application developers to align pipelines with system architecture, storage strategy, and reporting needs.
  • Implement data quality and validation checks and document data lineage and pipeline logic for audit and reuse.
  • Troubleshoot performance issues in data jobs and support data pipeline operations across environments (DEV, VAL, PROD).
  • Contribute CI/CD workflows and automation strategies to promote rapid iteration and secure deployment of data services.
  • Assist in developing or maintaining data documentation, including metadata, data dictionaries, and technical user guides.
  • Stay up to date with emerging technologies, techniques, and trends to inform product development and decision-making.

Minimum Qualifications:

  • Bachelor's degree in computer science, engineering, statistics, or related field.
  • 4+ years of experience in a data engineering, data pipeline, or ETL/ELT development role.
  • Strong proficiency in SQL, data transformation logic, and performance tuning for large datasets.
  • Proficiency with Python and libraries such as Pandas, PySpark, or Numpy.
  • Experience with modern version control and CI/CD practices (e.g., GitHub Actions, Jenkins).
  • Understanding of distributed computing solutions for data processing (e.g. AWS Glue, AWS EMR, Apache Hadoop, Apache Spark)
  • Experience with data pipeline orchestration frameworks or serverless tools (e.g., AWS StepFunctions, AWS Glue Workflows, and/or AWS Lambda).

Preferred Qualifications:

  • Experience developing solutions in AWS cloud environments (S3, Lambda, Aurora, SNS, CloudFormation/CDK).
  • Experience with Snowflake, Amazon RDS, or other cloud-native data warehouses.
  • Familiarity with modern data transformation tools (dbt, Dataform, or equivalent) and best practices for modular, tested SQL transformations within an ELT architecture.
  • Experience supporting healthcare data systems or CMS data environments
  • AWS certifications are a plus.