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Data Warehouse Developer Jobs in Pennsylvania (NOW HIRING)

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Oracle Developer with PL/SQL

Harrisburg, PA · On-site

$50 - $63.25/hr

Position : Sr. Data Warehouse Developer/ PL/SQL Database Developer Location : Harrisburg PA Duration: 2+ months Position Description: The position serves as a senior data warehouse developer in ...

Synergy Staffing

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Data Warehouse Analyst

Pittsburgh, PA · On-site

$85K - $105K/yr

... developer teams. Ensure that all system development, change control standards and compliance ... Working Knowledge of Data Warehousing, ETL processes and Data Security concepts * Employees must be ...

eTeam

Databricks Senior Data Engineer

Pittsburgh, PA · On-site

$111K - $133K/yr

Job Summary : eTeam is seeking a Databricks Senior Data Engineer to enhance their data architecture ... warehouse performance. Responsibilities : • Develop/Modify the architecture for the EDW ...

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How much do data warehouse developer jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for data warehouse developer in Pennsylvania is $54.56, according to ZipRecruiter salary data. Most workers in this role earn between $47.45 and $65.05 per hour, depending on experience, location, and employer.

What is a data warehouse developer?

A data warehouse developer designs and implements data warehouses, which are meant to store large amounts of data for easy retrieval by a business or organization. In this role, your duties are to develop storage architecture, design big data models, and create ways to input transactions, such as sales, receipts, customer data, and user downloads. Working with other developers, you ensure that the warehouse can both receive customer and client data and return it as output to analysts who can make recommendations based on their interpretation.

What are the key skills and qualifications needed to thrive as a data warehouse developer?

To thrive as a Data Warehouse Developer, you need expertise in data modeling, ETL processes, SQL, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Familiarity with data warehousing tools (such as Informatica, Talend, or SSIS), OLAP systems, and cloud data platforms is highly valuable, along with relevant certifications. Strong analytical thinking, problem-solving abilities, and effective communication skills set standout professionals apart in this role. These skills are crucial for designing efficient data solutions, ensuring data integrity, and enabling business intelligence for informed decision-making.

What are some common challenges data warehouse developers face when integrating data from multiple sources?

Data Warehouse Developers often encounter challenges with data consistency, varying data formats, and incomplete or poor-quality data when integrating information from multiple sources. Resolving these issues typically involves designing robust ETL (Extract, Transform, Load) processes, implementing data cleansing routines, and collaborating closely with data owners and business analysts to understand data lineage and requirements. Adapting to frequent changes in source systems and ensuring the warehouse remains scalable and performant can also be demanding, but they provide valuable opportunities to develop problem-solving skills and deepen technical expertise.

What is the difference between Data Warehouse Developer vs Data Analyst?

AspectData Warehouse DeveloperData Analyst
CredentialsBachelor's in Computer Science, Data Management, or related field; certifications like Microsoft Certified: Data Analyst AssociateBachelor's in Statistics, Mathematics, or related field; certifications like Microsoft Certified: Data Analyst Associate
Work EnvironmentDesigning, developing, and maintaining data warehouses; working with ETL tools and database systemsAnalyzing data sets, creating reports, and providing insights using BI tools
Industry UsageUsed across industries for data storage and managementUsed across industries for data analysis and reporting

The main difference is that Data Warehouse Developers focus on building and maintaining data storage systems, while Data Analysts interpret data to support business decisions. Both roles require strong technical skills and often overlap in data handling tasks, but their core responsibilities differ.

Is data warehouse a good career?

A career as a Data Warehouse Developer is in demand due to the increasing need for data management and analytics in organizations. It typically requires skills in SQL, ETL processes, and tools like Snowflake or Redshift, with opportunities for growth in data engineering and business intelligence roles.
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Data Warehouse Developer jobs near you
Infographic showing various Data Warehouse Developer job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $113,475 per year, or $54.6 per hour.

Informatica - Data Warehouse Developer

Cerebra Consulting, Inc.

Conshohocken, PA • On-site

$52.50 - $69/hr

Contractor

Posted 4 days ago

Job description

Title: Informatica Data Warehouse Developer with Informatica PowerCenter, SQL Server & Snowflake Schema's
Locations: Alpharetta, GA; Charlotte, NC; Chicago, IL; Conshohocken, PA; Denver, CO; Fargo, ND; Garden City, NY; Houston, TX; Lenexa, KS; Lubbock, TX; Morristown, NJ; Mt Juliet, TN; New York, NY; Purchase, NY; Topeka, KS - Hybrid 03 days per week
Duration: Long Term
We are looking for a skilled Data Warehouse Developer with strong experience in Informatica PowerCenter, SQL Server, and Snowflake. The ideal candidate will design, develop, and maintain ETL processes, optimize data pipelines, and support analytics/reporting needs.
Responsibilities:
  • Design and develop ETL workflows using Informatica PowerCenter.
  • Build and optimize complex queries using SQL Server.
  • Develop and manage data pipelines in Snowflake.
  • Perform data extraction, transformation, and loading (ETL) from multiple sources.
  • Optimize performance of ETL jobs and database queries.
  • Implement data quality checks and validation processes.
  • Work with business analysts and stakeholders to understand data requirements.
  • Maintain data models, data dictionaries, and documentation.

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