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Entry Level Databricks Data Engineer Jobs (NOW HIRING)

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 ...

New

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 ...

New

Data Engineer

Pittsburgh, PA · On-site

$111K - $133K/yr

S.) This role requires core experience and expertise on - Databricks (advanced, hands-on), Python, ETL/ELT pipeline development, Spark (SQL/PySpark). Job purpose * The Data Engineer will be ...

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 ...

New

Solutions Architect

Chicago, IL · On-site

$180K - $247K/yr

Mission Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data ...

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Analytica is seeking Data Engineers across multiple experience levels--from junior to senior--to ... Design, build, and maintain scalable data pipelines and data architectures using Databricks and ...

Job#: 3035030 Sr. Data Engineer - Databricks Location: Charlotte, North Carolina- 3X A WEEK HYBRID Employment Type: Contract Role Overview We are seeking a Sr. Data Engineer with expertise in ...

Azure Databricks Engineer

Iselin, NJ · On-site

$61 - $79.25/hr

Data Pipeline Development: * Build and maintain scalable ETL/ELT pipelines using Databricks ... Azure Data Engineer Associate or Databricks certified Data Engineer Associate certification ...

Data Engineer

Saint Louis, MO · Hybrid

$111K - $133K/yr

Scala, Pyspark, Databricks and AWS Role Overview: * Team Focus: Supports critical data ingestion ... Engineer with experience in Scala, Python or Java, Big Data+ AWS/Databricks. Needs AI agent ...

Data Engineer

Washington, DC

$129K - $155K/yr

Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related ... Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi

Data Engineer

Frisco, TX · On-site

$107K - $128K/yr

Data Engineer - GA UPDATE: 7 positions open!! 5 SUB SPOTS AVAILABLE!!! Location: Dunwoody, GA ... Utilize Databricks with Spark and Python/Scala for data transformation and analytics * Manage ...

DataOps Engineer

Montpelier, VT · On-site

$115K - $139K/yr

Databricks Data Engineer * Data Governance or Data Management certifications * Experience in healthcare, public sector, or highly regulated data environments * Familiarity with change management and ...

Entry Level Data Engineer

Dallas, TX

$113K - $136K/yr

... * Entry-level software programmers * Java Full stack developers * Python/Java developers * Data ... Snowflake, Databricks, LLM, Gen AI, text mining, Tableau, PowerBI, SAS, Tensorflow If you get ...

Data Engineer II

$117K - $140K/yr

As a Data Engineer II, you'll own the data platforms that power Samsara's GTM AI engine ... You'll be responsible for building, scaling, and optimizing our Databricks data store ...

Data Engineer

Bellevue, WA · On-site

$129K - $155K/yr

Data Engineer Job Location: Bellevue - Washington Job Type: Contract to Hire * Design build and ... Data Factory Databricks and Apache Spark * Develop and optimize ETLELT workflows to ingest ...

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Entry Level Databricks Data Engineer information

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How much do entry level databricks data engineer jobs pay per year?

As of Jun 13, 2026, the average yearly pay for entry level databricks data engineer in the United States is $69,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $78,500.00 per year, depending on experience, location, and employer.

What is an Entry Level Databricks Data Engineer?

An Entry Level Databricks Data Engineer is a professional who uses Databricks, a cloud-based data analytics platform, to design, build, and maintain data pipelines. They are responsible for preparing and processing large datasets, ensuring data quality, and enabling analytics and machine learning workflows. Typically, they work with tools such as Apache Spark, SQL, and Python, and collaborate with data analysts and data scientists to deliver data-driven solutions. As entry-level engineers, they are expected to have foundational knowledge of data engineering concepts and be eager to learn more advanced techniques on the job.

What are the key skills and qualifications needed to thrive as an Entry Level Databricks Data Engineer, and why are they important?

To thrive as an Entry Level Databricks Data Engineer, you need a foundational understanding of data engineering concepts, SQL, and Python or Scala, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (like AWS or Azure), and optional certifications such as Databricks Data Engineer Associate are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills help you collaborate with teams and solve complex data challenges. These skills and qualities are essential for building reliable data pipelines, ensuring data quality, and delivering actionable insights in a fast-paced environment.

What are some common challenges faced by entry-level Databricks Data Engineers, and how can they effectively overcome them?

Entry-level Databricks Data Engineers often face challenges such as learning to optimize Apache Spark jobs, managing complex data pipelines, and understanding cloud-based workflows. To overcome these, it's important to dedicate time to hands-on practice with Databricks notebooks, collaborate closely with more experienced engineers, and actively participate in code reviews and team discussions. Leveraging Databricks' extensive documentation and community forums can also help troubleshoot issues and stay updated on best practices.
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Data Engineer-Marketing Technology

Data Engineer-Marketing Technology

Foxit

Alpharetta, GA

$111K - $134K/yr

Full-time

Posted 2 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. 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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