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Data Warehouse Engineer Jobs in Georgia (NOW HIRING)

Data Engineer, Marketing Technology About Us: Foxit is remaking the way the world interacts with ... data warehouse (Databricks), licensing system, payment platform, and other source systems. Your ...

Data Engineer, Marketing Technology About Us: Foxit is remaking the way the world interacts with ... data warehouse (Databricks), licensing system, payment platform, and other source systems. Your ...

Data Integration Developer Department: Information Technology Location: Thomasville, GA Reports to ... Data Warehousing & Analytics * Develop and maintain stored procedures, database objects, and data ...

Lead Data Engineer

Atlanta, GA · On-site

$160K - $183K/yr

Engineer right-sized solutions for complex business problems focused on building patterns to support data pipelines, data warehousing, and data transformations. Apply knowledge of modern software ...

Azure Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Hands-on experience on Azure Platform including Data Factory, Synapse, Data Lake Gen2, CICD, DevOps. * Strong exp in SQL Server DB, SQL Server Data Warehouse. * Collaborate with project stakeholders ...

Data Engineer

Atlanta, GA · On-site

$77K - $176K/yr

As a data engineer, you know that organizing data can yield pivotal insights when it's gathered ... You Have: * 3+ years of experience in Data Warehouse development * 3+ years of experience with data ...

Data Engineer

Atlanta, GA · On-site

$77K - $176K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... You Have: * 3+ years of experience in Data Warehouse development * 3+ years of experience with data ...

Data Engineer

Atlanta, GA · On-site

$77K - $176K/yr

Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial ... You Have: * 3+ years of experience in Data Warehouse development * 3+ years of experience with data ...

Data Engineer

Atlanta, GA · On-site

$77K - $176K/yr

R0243232 Data Engineer The Opportunity: Ever-expanding technology like IoT, machine learning, and ... You Have: * 3+ years of experience in Data Warehouse develop ment * 3+ years of experience with ...

Works with application developers, business partners, management and Data Warehouse team. Extends ... Designs data warehouse or data mart fact tables, aggregate tables, and dimensions. Delivers quality ...

Principal Data Engineer

Alpharetta, GA · On-site

$107K - $129K/yr

... and Data Warehouse projects. Write, optimize, and automate complex SQL queries, T-SQL stored ... Mentor junior engineers on testing strategies, SQL best practices, and BI tool utilization.

Showing results 21-40

Data Warehouse Engineer information

See Georgia salary details

$73K

$106.8K

$135.5K

How much do data warehouse engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data warehouse engineer in Georgia is $106,814.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $115,300.00 per year, depending on experience, location, and employer.

What is a data warehouse engineer?

Data Warehouse Engineers are IT professionals who design, build, and maintain systems used for storing and analyzing large volumes of data. They create data models, implement ETL (Extract, Transform, Load) processes, and ensure data integrity and optimized performance within the data warehouse environment. Their work enables organizations to efficiently store data from various sources and make it accessible for business intelligence and analytics. Data Warehouse Engineers often collaborate with data analysts, data scientists, and database administrators to support informed decision-making.

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

AspectData Warehouse EngineerData Analyst
CredentialsBachelor's in CS, Data Science, or related; certifications like AWS, Google CloudBachelor's in Statistics, Math, or related; certifications like Microsoft Data Analyst
Work EnvironmentDesigning, building, maintaining data warehouses; working with ETL toolsAnalyzing data, creating reports, visualizations
Industry UsageUsed in organizations managing large-scale data infrastructureUsed across industries for business insights and decision-making

While both roles work with data, Data Warehouse Engineers focus on building and maintaining data storage systems, whereas Data Analysts interpret data to generate insights. They often collaborate but have distinct technical and functional responsibilities.

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

Data Warehouse Engineers often encounter challenges such as data inconsistency, varying data formats, and incomplete or duplicate records when integrating information from diverse systems. Addressing these issues requires careful planning, robust ETL (Extract, Transform, Load) processes, and close collaboration with source system owners and data analysts. Additionally, ensuring data quality and maintaining up-to-date documentation are crucial to support efficient troubleshooting and future scalability.

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

To thrive as a Data Warehouse Engineer, you need expertise in database design, ETL processes, SQL, and data modeling, typically supported by a degree in computer science or a related field. Familiarity with tools like Microsoft SQL Server, Oracle, Informatica, and cloud platforms such as AWS Redshift or Google BigQuery, as well as certifications in these technologies, are valuable. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with stakeholders and address data challenges efficiently. These skills ensure the reliable integration, storage, and retrieval of high-quality data, which is critical for business intelligence and decision-making.
What are the most commonly searched types of Data Warehouse Engineer jobs in Georgia? The most popular types of Data Warehouse Engineer jobs in Georgia are:
What are popular job titles related to Data Warehouse Engineer jobs in Georgia? For Data Warehouse Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Data Warehouse Engineer jobs in Georgia look for? The top searched job categories for Data Warehouse Engineer jobs in Georgia are:
What cities in Georgia are hiring for Data Warehouse Engineer jobs? Cities in Georgia with the most Data Warehouse Engineer job openings:
Infographic showing various Data Warehouse Engineer job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $106,814 per year, or $51.4 per hour.

Data Engineer-Marketing Technology

Foxit

Alpharetta, GA

$111K - $134K/yr

Full-time

Re-posted 27 days ago


Job description

                                                                    Data Engineer, Marketing Technology

About Us:

Foxit is remaking the way the world interacts with documents through advanced PDF technology and tools. We are a leading global software provider of fast, affordable, and secure PDF solutions that are used by millions of people worldwide. Winner of numerous awards, Foxit has customers in more than 200 countries and global operations. We have a complete product line and an exciting and aggressive development schedule. Our proven PDF technology is disrupting the status quo establishment and has accelerated our company growth. We are proud to list as customers Google and Amazon, and with your skills and help, we plan to add many more. Foxit has offices all over the world, including locations in the US, Asia, Europe, and Australia.
For more information, visit us @ www.foxit.com

About the Role

We are looking for an experienced Data Engineer to own the data pipelines that power our go-to-market systems. While this role is aligned to the marketing department's priorities, you will work day-to-day within our Business Applications & Data Analytics team, following the team's established development standards, architecture patterns, and code review processes. This ensures the pipelines you build are consistent with our broader data platform and maintainable by the wider engineering team.

Your primary focus will be marketing-related data needs - working closely with demand gen, product marketing, sales operations, and digital teams to understand their requirements, then building and maintaining the pipelines and integrations that deliver on them.

This is a hands-on execution role. You will build and operate the data infrastructure that connects our marketing automation platform (HubSpot), CRM (Salesforce), data warehouse (Databricks), licensing system, payment platform, and other source systems. Your work will directly support marketing's ability to segment audiences, measure attribution, and run data-driven campaigns at scale.

What You'll Do

Data Pipeline Development & Operations

Design, build, and maintain ETL/ELT pipelines, building upon and further optimizing our existing medallion architecture (Bronze Silver Gold) to move data between source systems (Salesforce CRM, HubSpot, NetSuite, Stripe, DealHub, LMS) and our Databricks data warehouse.

Build pipelines using PySpark and SQL in Databricks notebooks, following established development standards for naming, project structure, and layer-appropriate transformations.

Own the data sync layer between Databricks and HubSpot - enrichment flows inbound to HubSpot (license status, renewal dates, subscription state, firmographic data) and marketing engagement data flowing back to Databricks (email events, workflow enrollment, lifecycle changes).

Build and maintain Exchange layer pipelines that curate data for external system consumption, formatting and validating data to meet target system requirements.

Build and maintain scheduled batch jobs and event-driven integrations using APIs (REST, webhooks, OAuth).

Monitor pipeline health, set up alerting for failures and data quality degradation, and own incident response when syncs break.

Maintain documentation of data flows, integration architecture, and troubleshooting runbooks.

Data Modeling & Quality

Build and maintain dimensional models in Databricks (fact tables, dimension tables, bridge tables) following our data warehouse object type definitions and naming standards.

Work in collaboration with stakeholders and data analysts to build curated, business-ready tables and datamarts that apply business logic, KPI calculations, and aggregations optimized for analytics and campaign activation.

Implement identity resolution and deduplication logic to produce unified customer profiles from multiple source systems.

Establish data validation rules, quality checks, and monitoring to ensure accuracy and freshness of data flowing into marketing systems.

Normalize disparate data sources into clean centralized schemas with proper type enforcement, deduplication, and null handling.

Marketing Data & Segmentation Support

Ensure the data infrastructure supports audience segmentation, including firmographic, behavioral, and engagement signals.

Build the data layer that powers lifecycle marketing - triggered campaigns, dynamic journey branching, and personalization based on enriched customer profiles.

Support marketing and demand gen teams with reliable, accessible data for building audience targets in HubSpot.

Maintain data flows for email deliverability, subscription management, and suppression list synchronization.

Integration Development

Build and maintain API integrations between marketing, sales, and operational systems using Python and SQL.

Implement field-level transformation logic, sync orchestration, and error handling for system-to-system data flows.

Support website form and lead capture data flows - ensuring clean handoff from web properties into HubSpot and Databricks.

Work with third-party enrichment providers (firmographic, intent, technographic) to integrate enrichment data into automated workflows.

Reporting & Attribution

Build and maintain the data infrastructure that supports campaign attribution, channel performance analysis, and funnel reporting.

Ensure accurate data for conversion analytics, lead source tracking, and marketing ROI measurement.

Support centralized reporting by routing marketing engagement data back into Databricks for cross-functional analysis.

What You Bring

Required:

5+ years of experience in data engineering, with hands-on pipeline development and production operations.

Strong proficiency in SQL and Python/PySpark for data pipeline development.

Experience building and maintaining ETL/ELT pipelines using Databricks, dbt, Airflow, Azure Data Factory, or equivalent.

Hands-on experience with cloud data platforms - Databricks, Snowflake, BigQuery, or Redshift.

Solid understanding of dimensional data modeling - fact tables, dimension tables, schema design, and data warehouse concepts.

Experience with medallion or layered data architectures (raw cleansed business-ready), Kimball-style star schemas, and one-big-table approaches to data modeling.

Working knowledge of API integration patterns - REST, webhooks, OAuth, batch sync architectures.

Experience with CRM platforms (Salesforce, HubSpot, or similar), marketing automation systems, and CPQ/quoting tools (DealHub or similar).

Bachelor's degree in Computer Science, Information Systems, or equivalent industry experience.

Preferred:

Experience with Databricks (Delta Lake, PySpark, Unity Catalog).

Familiarity with HubSpot APIs and data model.

Experience with identity resolution and customer data deduplication across multiple source systems.

Exposure to marketing data concepts - lead scoring, audience segmentation, campaign attribution, lifecycle stages.

Experience with Azure cloud services (Azure Functions, Azure DevOps, Azure Data Factory).

Knowledge of data security and privacy practices, particularly regarding PII handling.

Experience with code review processes and development standards compliance in a collaborative data engineering team.

What Sets You Apart

You've built and operated production data pipelines that marketing teams depend on daily - you understand the impact of data freshness and accuracy on campaign execution.

You're comfortable working within a marketing department and can translate data requests from non-technical stakeholders into pipeline requirements.

You take ownership of pipeline reliability - building monitoring and alerting proactively rather than waiting for someone to report a problem.

You've worked with multiple data sources and know how to handle the messiness of real-world identity resolution and deduplication.

Why Join Us

High-impact work. Your pipelines will directly power how our marketing engine operates and scales.

Modern stack. Databricks, Delta Lake, PySpark, HubSpot, Python, SQL - you'll work with current tools, not legacy systems.

Room to build. We're investing in our data infrastructure as part of a major platform migration, and you'll shape how it's built.

Collaborative environment. You'll work closely with marketing, sales, and IT teams - visible, cross-functional work without being siloed.

Foxit is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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