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Databricks Data Engineer Jobs in Houston, TX (NOW HIRING)

Public Health Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Guidehouse seeks a Data Engineer to support the development, maintenance, and enhancement of data ... Exposure to Databricks, Spark, or large-scale data processing technologies. * Familiarity with AWS ...

Senior Data Engineer

Houston, TX · On-site

$95K - $130K/yr

Strong experience with modern data platforms such as Microsoft Fabric, Snowflake, or Databricks is ... engineering * Experience with modern cloud data platforms (Fabric, Snowflake, or Databricks)

Extensive experience working with Databricks. * Working knowledge of the Alation data governance tool. * Strong skills in SQL (T-SQL), Python (PySpark/Pandas), DAX, Power Query (M), PL/SQL.

Extensive experience working with Databricks. * Working knowledge of the Alation data governance tool. * Strong skills in SQL (T-SQL), Python (PySpark/Pandas), DAX, Power Query (M), PL/SQL.

Sr Data Engineer

Houston, TX · On-site

$109K - $131K/yr

You will work hands-on with modern data technologies such as Amazon Redshift, Databricks, and cloud ... You will apply strong software engineering principles to optimize data ingestion, transformation ...

Sr Data Engineer

Houston, TX · On-site

$109K - $131K/yr

You will work hands-on with modern data technologies such as Amazon Redshift, Databricks, and cloud ... You will apply strong software engineering principles to optimize data ingestion, transformation ...

Job Title:- Azure Data Engineer Location:- Spring Texas (On-Site) Need Only Local to Houston, TX ... Advanced SQL Snowflake Tamr Python GitHub Intermediate Databricks Airflow

Showing results 41-60

Databricks Data Engineer information

See Houston, TX salary details

$42.5K

$123.8K

$169.4K

How much do databricks data engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for databricks data engineer in Houston, TX is $123,818.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $131,200.00 per year, depending on experience, location, and employer.

What is a Databricks data engineer?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

What does a Databricks data engineer do?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.

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

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

How much does a Databricks data engineer make?

A Databricks Data Engineer typically earns between $90,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with advanced skills in Spark, cloud platforms, and data pipeline development can earn higher salaries.

Is a Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and big data processing. Skills in Apache Spark, cloud environments, and data pipeline development are highly sought after, leading to strong job growth in this field.

What are the most commonly searched types of Databricks Data Engineer jobs in Houston, TX?

The most popular types of Databricks Data Engineer jobs in Houston, TX are:

What are popular job titles related to Databricks Data Engineer jobs in Houston, TX?

For Databricks Data Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Databricks Data Engineer jobs in Houston, TX look for?

The top searched job categories for Databricks Data Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Databricks Data Engineer jobs?

Cities near Houston, TX with the most Databricks Data Engineer job openings:

Infographic showing various Databricks Data Engineer job openings in Houston, TX as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $123,818 per year, or $59.5 per hour.

Forward Deployed Data Engineer - Houston

Houston, TX • On-site

$180K - $230K/yr

Full-time

Posted 10 days ago


Job description

The Opportunity

As a Forward Deployed Data Engineer (FDE) on our US Launch Team, you will act as the principal technical anchor embedded directly within high-stakes enterprise client accounts (focusing heavily on Financial Services and Healthcare). You won't just be writing specs or advising from afar-you will be on the front lines in client environments, bridging the gap between C-suite data strategy and hands-on production code.

Working at the tip of the spear alongside our elite partners at Databricks and Anthropic, you will lead architecture design, modernize brittle legacy ecosystems into cloud-native Lakehouses, build agentic AI data harnesses, and guide integrated "SWAT" pods to ship working software in weeks rather than months.

Key Responsibilities
  • Embedded Technical Leadership: Serve as the primary technical authority on client engagements. Partner directly with client VP/CTO stakeholders to scope architectures, map data domains, and turn complex requirements into execution-ready engineering plans.

  • Hands-On Lakehouse Modernization: Roll up your sleeves to write and optimize production PySpark, Databricks SQL, and Delta Live Tables (DLT)-actively refactoring complex legacy logic (Informatica, PL/SQL, legacy stored procedures) into Medallion Architectures.

  • Agentic AI & Data Infrastructure: Architect deterministic, secure data "harnesses" that integrate LLM workflows (Anthropic/Claude) into traditional enterprise data pipelines safely and cost-effectively.

  • DataOps & IaC Ownership: Write modular Terraform scripts to provision cloud environments (AWS/GCP), manage governance and lineage via Unity Catalog, and enforce CI/CD rigor across projects.

  • Pod & Delivery Guidance: Partner with our LATAM-based nearshore engineering squads (600+ experts) as the US technical lead-conducting code reviews, debugging performance bottlenecks, and maintaining high engineering standards.

  • Technical Unblocking & Escalation: Act as the ultimate technical safety net. If a pipeline breaks or a deployment stalls at 2:00 AM, you have the hands-on depth to jump into the code, fix the issue, and keep client delivery on track.

Qualifications & Requirements

Technical Mastery & Execution

  • Extensive Hands-On Data Engineering: Deep proficiency in Python and advanced SQL with a proven track record of shipping production data software.

  • Deep Databricks Platform Expertise: Hands-on experience building, scaling, and tuning Databricks Lakehouse environments (Delta Lake, Unity Catalog, PySpark, DLT, Workflows).

  • Modern Stack & IaC Discipline: Expert-level experience with dbt (Core or Enterprise) for data modeling, Terraform for Infrastructure as Code, and Git/Airflow for orchestration and CI/CD.

  • Legacy Migration Experience: Demonstrated background migrating enterprise client workloads from legacy platforms (Teradata, Netezza, Informatica, Oracle) to modern cloud infrastructure.

Client Presence & Startup Grit

  • The "Player-Coach" Mindset: Equal comfort pitching target architectures to a client CTO and debugging a failing PySpark job or dbt macro alongside junior engineers.

  • Executive Communication: Ability to translate messy business requirements into clean architectural patterns and speak authoritatively across both technical and business functions.

  • Scrappy Nation-Builder: High autonomy and resilience-thriving in a fast-paced, Series A growth environment without relying on rigid corporate playbooks or large support structures.

Nice-to-Haves

  • Prior experience in forward-deployed, technical consulting, or ProServe roles at top-tier agencies or hyper-growth vendors.

  • Pragmatic experience building or deploying LLM/GenAI orchestration frameworks (LangChain, LlamaIndex, Anthropic API) into production pipelines.

  • Official certifications in Databricks, AWS, GCP, or dbt.

The anticipated base salary range for this role is $180,000 - $230,000. In addition to base pay, this position may be eligible for an annual discretionary bonus. An individual's final salary offer will be determined based on a variety of factors, including geographic location, experience, specialized skills, and qualifications. This compensation range is subject to updates or modifications at the company's discretion