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Data Warehouse Developer Jobs in Houston, TX (NOW HIRING)

Power BI Developer Location: Spring TX - Hybrid Duration: 6-12 months The Power BI Developer ... Provide expertise in data management, warehousing, and business intelligence, both functionally and ...

As a BI Data Engineer, you will design data storage systems, works to fill them with quality data using data pipelines into a data warehouse. The BI will be responsible for expanding and optimizing ...

As a BI Data Engineer, you will design data storage systems, works to fill them with quality data using data pipelines into a data warehouse. The BI will be responsible for expanding and optimizing ...

Snowflake Data Engineer - W2

Spring, TX · On-site

$96K - $116K/yr

We are looking for a hands-on Data Analytics Engineer with strong experience in DBT, Snowflake, and ... warehouse concepts. - Ability to work effectively in a collaborative, cross-functional team ...

Houston TX Duration: 9 Months Skillsets: • 8 years of experience as a Data Warehouse Analyst • ... The candidate will not be developing dashboards himself but must support the developers and for ...

Showing results 21-40

Data Warehouse Developer information

See Houston, TX salary details

$12

$50

$67

How much do data warehouse developer jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for data warehouse developer in Houston, TX is $50.80, according to ZipRecruiter salary data. Most workers in this role earn between $44.18 and $60.58 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.

What are popular job titles related to Data Warehouse Developer jobs in Houston, TX?

For Data Warehouse Developer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Data Warehouse Developer jobs in Houston, TX look for?

The top searched job categories for Data Warehouse Developer jobs in Houston, TX are:

Infographic showing various Data Warehouse Developer job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $105,658 per year, or $50.8 per hour.

$101K - $137K/yr

Full-time

Re-posted 23 days ago


Job description

Job Summary:
Fracht Group - North America is seeking a Senior Data Engineer who will design, build, and own the enterprise data platform to enhance analytics and data-driven decision-making across global operations. The role involves engineering data pipelines, modeling data for analytical workloads, and collaborating with business stakeholders to translate requirements into technical specifications.
Responsibilities:
• Designs, builds, and maintains end-to-end data pipelines across the Microsoft Fabric medallion architecture (Bronze, Silver, Gold, and Warehouse) using Spark and PySpark notebooks orchestrated through Fabric Data Pipelines.
• Develops and owns ingestion from multiple heterogeneous source systems, including transactional and TMS databases, CosmosDB document stores, and file-based feeds, applying appropriate replication strategies (Change Data Capture, mirrored or current-state replication, and watermark-based incremental loads).
• Implements robust ELT and ETL patterns: incremental and full-load logic, idempotent MERGE operations, surrogate-key generation, deduplication, typed-NULL handling, and runtime parameterization of load identifiers and lakehouse targets.
• Optimizes pipeline performance, compute and capacity usage, and cost, and ensures the platform scales reliably for a global user base.
• Designs dimensional models (star schema, fact and dimension tables, bridge tables, and slowly changing dimensions) in the Fabric Data Warehouse to support analytical and reporting workloads.
• Authors and maintains performant T-SQL stored procedures, views, and warehouse tables with explicit, well-documented contracts (explicit column lists, typed columns, and semantic ordering).
• Defines data requirements and business logic for new data products and translates them into sound, maintainable warehouse structures.
• Creates and optimizes Power BI semantic models over the warehouse, including complex DAX measures and calculated columns, time intelligence, and Direct Lake or Import configurations.
• Designs, implements, and troubleshoots Row-Level Security (RLS) and user access controls across multiple organizational levels and tenants, including embedded scenarios.
• Provides the engineering foundation for interactive dashboards and supports BI developers and analysts consuming the platform.
• Performs comprehensive data reconciliation and validation, identifies and root-causes discrepancies and anomalies, and remediates defects across the pipeline.
• Owns production incident response for data pipelines and semantic-model refreshes, diagnosing failures, restoring service, and implementing durable fixes.
• Tests changes thoroughly before deployment to ensure accuracy, performance, and functionality across scenarios and environments.
• Establishes and enforces deployment discipline across Dev, UAT, and Production, including source control (Git), branch protection, promotion rules, and release governance for internal and vendor contributors.
• Creates and maintains comprehensive technical documentation covering data sources, lineage, relationships, DAX measures, business logic, runbooks, and known issues, accessible to both technical and non-technical audiences.
• Configures monitoring, alerting, and validation routines on critical pipelines and contributes to the team's standards, patterns, and knowledge base.
• Works directly with global business stakeholders to gather requirements and translate them into technical specifications and data products.
• Coordinates with and provides technical oversight of external delivery vendors, and participates in and may lead sprint planning, grooming, and effort estimation.
• Stays current with Microsoft Fabric, Power BI, and industry trends; evaluates and recommends new tools and approaches; builds reusable components and frameworks; mentors junior team members; and responds to stakeholder communications within the same business day.
• Performs other related duties as assigned.
Qualifications:
Required:
• Bachelor's degree required in Computer Science, Data Engineering, Software Engineering, Information Systems, Data Analytics, or a closely related technical field.
• Minimum of 5 years of progressive experience in data engineering, analytics engineering, or business intelligence; or a Master's degree in a related field plus a minimum of 3 years of relevant specialized experience.
• Demonstrated experience building production data pipelines and dimensional data warehouses on cloud-based data platforms (Microsoft Fabric and/or Azure).
• Proven experience developing complex Power BI semantic models and Row-Level Security in enterprise, multi-site environments.
• Experience working with both cloud and on-premises source systems, and creating and maintaining technical documentation.
• Advanced proficiency with Microsoft Fabric components: Workspaces, OneLake, Lakehouse, Data Warehouse, Data Pipelines, Notebooks, and Semantic Models.
• Strong hands-on Spark and PySpark for large-scale data transformation in notebooks.
• Expert-level SQL and T-SQL for complex queries, stored procedures, optimization, and analysis.
• Proficiency with dbt (data build tool) for SQL-based transformations, including model development, incremental materialization strategies, testing, documentation generation, and integration with version-controlled deployment workflows.
• Advanced knowledge of DAX, including complex measures, time intelligence, and optimization; proficiency with Tabular Editor, ALM Toolkit, and DAX Studio.
• Strong command of data-warehouse and dimensional-modeling concepts: medallion architecture, star schema, fact, dimension, and bridge design, slowly changing dimensions, surrogate keys, and incremental-load patterns.
• Working knowledge of data-replication mechanisms (Change Data Capture and mirrored or current-state replication) and their analytical trade-offs.
• Proficiency in Power Query (M) and Microsoft Excel for data preparation; familiarity with Dataflows Gen2 and/or Azure Data Factory.
• Experience with version control (Git) and deployment and CI/CD practices for data and BI solutions, including environment promotion (Dev to UAT to Prod).
• Familiarity with Azure and Microsoft Entra ID, workspace governance, and Fabric capacity and licensing concepts.
• Excellent technical-writing skills for clear, comprehensive documentation, and strong analytical and troubleshooting ability on complex technical issues.
• Exceptional attention to detail and a strong commitment to data accuracy.
• Excellent written and verbal communication, with the ability to translate complex technical concepts for non-technical stakeholders and present to varied audiences.
• Self-motivated, organized, and able to manage multiple priorities and deadlines, working independently with minimal supervision.
• Collaborative team player with a positive, knowledge-sharing attitude and a strong service orientation.
Preferred:
• Master's degree in Computer Science, Data Analytics, Business Analytics, Information Systems, or a related field is strongly preferred.
• Experience supporting global or multi-site organizations preferred.
• Experience with logistics, supply chain, or freight-forwarding systems (such as CargoWise) is a plus.
• Relevant advanced certifications (Fabric Data Engineer Associate DP-700, Fabric Analytics Engineer Associate DP-600, Azure Data Engineer Associate DP-203) are a plus.
Company:
The Fracht Group is an international freight forwarder and an industry leader in providing general and specialized logistics solutions. Founded in 1955, the company is headquartered in Houston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.