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Senior Databricks Data Engineer Jobs in Red Bank, NJ

Dlapiper

Data Engineer

New York, NY

$125K - $150K/yr

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Sigma Computing

Data Engineer

New York, NY · On-site

$140K - $180K/yr

As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both ...

Tatari

Senior Data Engineer

New York, NY · On-site

$170K - $200K/yr

As a Senior Data Engineer in our Reporting and Measure pillar, you will design, build and own the ... We use Databricks and Delta Lake here * Experience with workflow orchestration tools such as ...

Tatari

Senior Data Engineer

New York, NY · Hybrid

$170K - $200K/yr

As a Senior Data Engineer in our Reporting and Measure pillar, you will design, build and own the ... We use Databricks and Delta Lake here * Experience with workflow orchestration tools such as ...

Bedrock Robotics

Data Engineer

New York, NY · On-site

$125K - $150K/yr

We need a Senior Data Engineer who can work across the stack: tighten up our ingestion pipelines ... Hands-on experience with Databricks and Spark * Experience with streaming or near-real-time ...

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All JobsDatabricks Data Engineer JobsSenior Databricks Data Engineer JobsSenior Databricks Data Engineer Jobs in Red Bank, NJ

Senior Databricks Data Engineer information

See Red Bank, NJ salary details

$61.1K

$129.9K

$188.3K

How much do senior databricks data engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for senior databricks data engineer in Red Bank, NJ is $129,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,200.00 and $147,300.00 per year, depending on experience, location, and employer.

How does a Senior Databricks Data engineer typically collaborate with data scientists and analysts on large-scale projects?

A Senior Databricks Data Engineer works closely with data scientists and analysts to design, build, and optimize data pipelines that enable advanced analytics and machine learning initiatives. They often participate in cross-functional meetings to understand data requirements, translate them into scalable ETL processes, and ensure data quality and accessibility. Regular collaboration also involves troubleshooting data issues, optimizing Spark jobs for performance, and sharing best practices for data management. This close teamwork ensures that analytical teams have reliable, timely, and well-structured data to drive insights and decision-making.

What are the key skills and qualifications needed to thrive as a Senior Databricks Data engineer, and why are they important?

To thrive as a Senior Databricks Data Engineer, you need advanced expertise in data engineering concepts, big data technologies, and proficiency in programming languages like Python or Scala, usually backed by a bachelor's degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (Azure, AWS, or GCP), and certifications like Databricks Certified Data Engineer are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams distinguish top performers in this role. These skills are essential to efficiently design scalable data solutions, optimize data workflows, and drive business insights in complex data environments.

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

AspectSenior Databricks Data EngineerData Engineer
CredentialsTypically requires experience with Databricks, Spark, cloud platforms, and often certifications like Databricks Certified Data Engineer AssociateRequires knowledge of data pipelines, SQL, ETL tools, and often cloud platform experience, but less specialized in Databricks
Work EnvironmentWorks primarily within Databricks environment, focusing on big data processing and analyticsWorks across various data tools and platforms, including traditional ETL and cloud services
Industry UsageCommon in organizations leveraging Databricks for big data analytics and machine learningWidely used across industries for general data pipeline development and data management

The main difference is that a Senior Databricks Data Engineer specializes in using Databricks and Spark for big data solutions, often requiring specific certifications and experience. A Data Engineer has a broader focus on data pipeline development across various tools and platforms, with less emphasis on Databricks-specific skills.

What is a Senior Databricks Data engineer?

Senior Databricks Data Engineers are experienced professionals who design, develop, and optimize large-scale data processing pipelines using the Databricks platform. They work with big data technologies like Apache Spark, Delta Lake, and cloud platforms such as Azure or AWS. Their responsibilities include building and maintaining ETL processes, ensuring data quality, and collaborating with data scientists and analysts to deliver reliable, high-performance data solutions. As senior engineers, they also mentor junior team members and contribute to architectural decisions.
What are popular job titles related to Senior Databricks Data Engineer jobs in Red Bank, NJ? For Senior Databricks Data Engineer jobs in Red Bank, NJ, the most frequently searched job titles are:
What cities near Red Bank, NJ are hiring for Senior Databricks Data Engineer jobs? Cities near Red Bank, NJ with the most Senior Databricks Data Engineer job openings:
Senior Databricks Data Engineer jobs near you
Infographic showing various Senior Databricks Data Engineer job openings in Red Bank, NJ as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $129,877 per year, or $62.4 per hour.

Senior Data Engineer with MDM experience

Realtech Services

New York, NY • On-site

$116K - $157K/yr

Full-time

Re-posted 13 days ago

Job description


We are seeking a highly skilled and experienced Senior Data Engineer specializing in Master Data Management (MDM) to join our data team. The ideal candidate will have a strong background in designing, implementing, and managing end-to-end MDM solutions, preferably within the financial sector. Candidate will be responsible for architecting robust data platforms, evaluating MDM tools, and aligning data strategies to meet business needs.
Responsibilities:
Lead the design, development, and deployment of comprehensive MDM solutions across the organization, with an emphasis on financial data domains.
Demonstrate extensive experience with multiple MDM implementations, including platform selection, comparison, and optimization.
Architect and present end-to-end MDM architectures, ensuring scalability, data quality, and governance standards are met.
Evaluate various MDM platforms (e.g., Informatica, Reltio, Talend, IBM MDM, etc.) and provide objective recommendations aligned with business requirements.
Collaborate with business stakeholders to understand reference data sources and develop strategies for managing reference and master data effectively.
Implement data integration pipelines leveraging modern data engineering tools and practices.
Develop, automate, and maintain data workflows using Python, Airflow, or Astronomer.
Build and optimize data processing solutions using Kafka, Databricks, Snowflake, Azure Data Factory (ADF), and related technologies.
Design microservices, especially utilizing GraphQL, to enable flexible and scalable data services.
Ensure compliance with data governance, data privacy, and security standards.
Support CI/CD pipelines for continuous integration and deployment of data solutions.
Requirements:
12+ years of experience in data engineering, with a proven track record of MDM implementations, preferably in the financial services industry.
Extensive hands-on experience designing and deploying MDM solutions and comparing MDM platform options.
Strong functional knowledge of reference data sources and domain-specific data standards.
Expertise in Python, Pyspark, Kafka, microservices architecture (particularly GraphQL), Databricks, Snowflake, Azure Data Factory, SQL, and orchestration tools such as Airflow or Astronomer.
Familiarity with CI/CD practices, tools, and automation pipelines.
Ability to work collaboratively across teams to deliver complex data solutions.
Experience with financial systems (capital markets, credit risk, and regulatory compliance applications).
Preferred, but not required:
Familiarity with financial data models and regulatory requirements.
Experience with Azure cloud platforms
Knowledge of data governance, data quality frameworks, and metadata management.