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Overnight Databricks Data Engineer Jobs in Georgia

Data Engineer, Marketing Technology About Us Foxit is remaking the way the world interacts with ... Own the data sync layer between Databricks and HubSpot - enrichment flows inbound to HubSpot ...

Data Engineer-Marketing Technology

Alpharetta, GA · On-site

$111K - $134K/yr

Data Engineer, Marketing Technology About Us: Foxit is remaking the way the world interacts with ... Own the data sync layer between Databricks and HubSpot -- enrichment flows inbound to HubSpot ...

Data Engineer-Marketing Technology

Alpharetta, GA · On-site

$111K - $134K/yr

Data Engineer, Marketing Technology About Us: Foxit is remaking the way the world interacts with ... Data Modeling & Quality • Build and maintain dimensional models in Databricks (fact tables ...

Data Engineer

Atlanta, GA · On-site

$60 - $68/hr

Top Skills' Details 1- Databricks data modeling w/ Python 2- Azure ETL / Data analysis 3- Spark/Hive/Airflow 5-10 Years Focused on manipulating data in a software engineering capacity. Some of that ...

Azure Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

ADLS Gen2, Azure Data Factory, Azure Databricks, Synapse Analytics,Azure DevOps:-Boards, Repos, Pipelines, Test Plans * Databases: * Must Have: SQL servers/SQL databases, MongoDB, * BI Platforms:

Lead Data Engineer

Atlanta, GA · On-site

$120 - $160/hr

Job Summary Join us as a Lead Data Engineer on the Corporate Data Technology Team. Become an ... Develop secure, high‑quality production code and data pipelines on Databricks, reviewing and ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on ... Develop data processing solutions using Azure Databricks and PySpark. * Write, optimize, and ...

... Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data models and data flow diagrams ...

Databricks Engineer

Louisville, GA · On-site

$45K - $110K/yr

DataBricks - Data Engineering. Experience: 3-5 Years. The expected compensation for this role ranges from $45,000 to $110,000 . Final compensation will depend on various factors, including your ...

Highly proficient in Cloud platforms (AWS preferred, Azure considered), Databricks (5-6 years), Python, and SQL, with hands-on experience applying fundamental data engineering practices. * Deep ...

Showing results 21-40

Overnight Databricks Data Engineer information

What is an overnight Databricks data engineer?

An Overnight Databricks Data Engineer is a professional who works primarily during night shifts to manage, design, and maintain big data pipelines and workflows using Databricks, a cloud-based data analytics platform. Their responsibilities often include developing and optimizing data processing jobs, ensuring data quality, and troubleshooting issues that arise during overnight data operations. This role is critical for organizations that require 24/7 data processing, continuous ETL jobs, or real-time analytics. Working overnight may also involve monitoring automated systems, performing scheduled data loads, and collaborating with global teams to ensure data availability and reliability.

What skills and qualifications are needed to thrive as an overnight Databricks data engineer?

To thrive as an Overnight Databricks Data Engineer, you need strong proficiency in data engineering, Python or Scala programming, and experience with big data technologies, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and certifications like Databricks Certified Data Engineer are highly valued. Attention to detail, problem-solving, and effective communication are essential soft skills, especially for troubleshooting and collaborating across shifts. These competencies ensure reliable data pipeline management and efficient resolution of issues during off-hours, maintaining seamless business operations.

What unique challenges do overnight Databricks data engineers face, and how can they be addressed?

Overnight Databricks Data Engineers often work with limited real-time support, which can present challenges when troubleshooting urgent data pipeline issues or system outages. To address this, it’s essential to develop strong problem-solving skills, document processes thoroughly, and leverage automated monitoring and alerting tools. Additionally, close collaboration with daytime teams during handoff periods ensures continuity and minimizes disruptions. Building a habit of proactive communication and maintaining detailed logs helps the entire team resolve issues efficiently and maintain data quality.

What is the difference between Overnight Databricks Data Engineer vs Data Engineer?

AspectOvernight Databricks Data Engineer
Work EnvironmentPrimarily remote or on-site, working overnight shifts to support global data operations
CertificationsDatabricks certifications, cloud platform credentials (AWS, Azure), data engineering certifications
Tools & TechnologiesDatabricks platform, Spark, cloud services, SQL, Python, ETL tools
Industry UsageTech, finance, healthcare, retail with 24/7 data needs

While both roles focus on data engineering, the Overnight Databricks Data Engineer specializes in managing data pipelines on the Databricks platform during overnight shifts, often supporting global operations. A Data Engineer may work across various platforms and shifts, with broader responsibilities in data architecture and pipeline development. The overnight role emphasizes specific platform expertise and shift timing, catering to organizations with continuous data processing needs.

What are the most commonly searched types of Databricks Data Engineer jobs in Georgia?

The most popular types of Databricks Data Engineer jobs in Georgia are:

What cities in Georgia are hiring for Overnight Databricks Data Engineer jobs?

Cities in Georgia with the most Overnight Databricks Data Engineer job openings:

Data Engineer-Marketing Technology

Foxit

Alpharetta, GA • On-site

$100 - $130/hr

Other

Re-posted 28 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 at 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 to Silver to 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 to cleansed to 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.

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