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Manager Databricks Data Engineer Jobs in Bear, DE

Data Engineer

Aberdeen Proving Ground, MD · Hybrid

$122K - $147K/yr

Data Engineer Location: 6560 Surveillance Loop, Building 6007, Aberdeen Proving Ground, Maryland ... monitor, test, manage, modernize, evaluate and sustain fielded and enterprise-hosted MC ...

Databricks Lead

Chester, PA · On-site

$57 - $74.50/hr

Experience cloud/on-prem devops tools for orchestration, scheduling, logging, required for data ... Proven ability to manage multiple complex projects and deliver high-quality results. * Strong ...

Data Innovation Lab Data Engineer Fellowship * Join an innovative, like-minded team that focuses on ... Create and manage Cloud services (Azure, AWS) to support all aspects of our tech products ...

Lead Data Engineer

Wilmington, DE · On-site

$111K - $133K/yr

Lead Data Engineer Do you love building and pioneering in the technology space? Do you enjoy ... Collaborate with digital product managers, and deliver robust cloud-based solutions that drive ...

Lead Data Engineer

Wilmington, DE · On-site

$111K - $133K/yr

Lead Data Engineer Do you love building and pioneering in the technology space? Do you enjoy ... Collaborate with digital product managers, and deliver robust cloud-based solutions that drive ...

Lead Data Engineer

Wilmington, DE · On-site

$111K - $133K/yr

Lead Data Engineer Do you love building and pioneering in the technology space? Do you enjoy ... Collaborate with digital product managers, and deliver robust cloud-based solutions that drive ...

Lead Data Engineer

Wilmington, DE · On-site

$111K - $133K/yr

Lead Data Engineer Do you love building and pioneering in the technology space? Do you enjoy ... Collaborate with digital product managers, and deliver robust cloud-based solutions that drive ...

Showing results 21-40

Manager Databricks Data Engineer information

See Bear, DE salary details

$42.8K

$124.8K

$170.7K

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

As of Aug 22, 2026, the average yearly pay for manager databricks data engineer in Bear, DE is $124,755.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,100.00 and $132,200.00 per year, depending on experience, location, and employer.

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

AspectManager Databricks Data EngineerData Engineer
Primary FocusTeam leadership, project management, strategic planningData pipeline development, data modeling, ETL processes
Required SkillsLeadership, Databricks platform knowledge, data architectureSQL, Spark, Python, cloud platforms
CertificationsDatabricks certifications, leadership credentialsDatabricks certifications, technical skills
Work EnvironmentManagement, cross-team collaboration, strategic oversightHands-on data processing, coding, pipeline implementation

The Manager Databricks Data Engineer oversees data engineering teams and manages projects on the Databricks platform, focusing on strategy and leadership. In contrast, a Data Engineer primarily handles technical tasks like building data pipelines and coding. Both roles require Databricks platform knowledge and relevant certifications, but the managerial role emphasizes leadership and project management, while the Data Engineer role is more technical and execution-focused.

How much does a Manager Databricks Data Engineer make?

A Manager Databricks Data Engineer typically earns between $120,000 and $160,000 annually, depending on experience, location, and company size. They often require strong skills in Spark, SQL, and cloud platforms like Azure or AWS, along with leadership responsibilities. Compensation may also include bonuses and stock options.

Is a Manager Databricks Data Engineer in demand?

Manager Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for advanced data processing skills. They typically require expertise in Spark, SQL, and cloud environments, making their roles critical in data-driven organizations seeking scalable analytics solutions.

What are the most commonly searched types of Databricks Data Engineer jobs in Bear, DE?

The most popular types of Databricks Data Engineer jobs in Bear, DE are:

What are popular job titles related to Manager Databricks Data Engineer jobs in Bear, DE?

For Manager Databricks Data Engineer jobs in Bear, DE, the most frequently searched job titles are:

Infographic showing various Manager Databricks Data Engineer job openings in Bear, DE as of August 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $124,755 per year, or $60 per hour.

Lead Software Engineer - Databricks

J.P. Morgan

Wilmington, DE

Full-time

Medical, Retirement

Re-posted 12 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead Software Engineer-Databricks at JPMorgan Chase within our Corporate Sector's Enterprise Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

       Job responsibilities

  • Lead the architecture and delivery of high-throughput, low-latency data pipelines on Databricks using Apache Spark (Core, SQL, Structured Streaming), driving performance, reliability, and scalability.
  • Establish and evolve Lakehouse patterns with Delta Lake (ACID transactions, schema evolution, time travel, Z-ordering, compaction) to ensure performant, maintainable data platforms at scale.
  • Own Databricks cluster strategy and configuration, including runtime selection, autoscaling, driver/executor sizing, Spark configurations, init scripts, cluster policies, pools, and instance profiles.
  • Orchestrate and automate pipelines and jobs using Databricks Workflows, integrating with AWS eventing and orchestration services as needed.
  • Design secure ingestion and transformation frameworks leveraging Databricks services, including Delta or unmanaged table design, ingestion task creation, and Airflow DAGs to produce trusted and refined datasets.
  • Enforce data quality, lineage, and governance using Unity Catalog and/or AWS Glue Catalog, embedding expectations and validation directly into pipelines.
  • Drive Spark and Databricks performance engineering and tuning (partitioning and file sizing, AQE, broadcast joins, shuffle tuning, caching, spill/memory control, job right-sizing, and liquid clustering/partitioning keys) to optimize cost and throughput.
  • Build and maintain reusable libraries, frameworks, and APIs in Python and/or Java, ensuring strong unit, integration, and data validation test coverage.
  • Implement CI/CD for data projects using Git-based workflows, Terraform-based infrastructure deployments and environment promotion, and automated releases; champion engineering standards, code reviews, and enterprise-authorized AI-assisted engineering practices (e.g., code review/refactoring, test acceleration, and incident/root-cause analysis) with consistent validation (secure coding, peer review, automated testing) and reuse of proven patterns.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

    Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience. 
  • Advanced experience in software engineering and data engineering, including significant production delivery with Apache Spark on Databricks and/or AWS EMR.
  • Advanced hands-on Databricks expertise across Delta Lake, Unity Catalog, Workflows, Repos/notebooks, and SQL Warehouses, including cluster configuration and optimization.
  • Proven ability to architect, build, and operate reliable ETL/ELT data pipelines (batch and streaming), including schema design/evolution, SLAs, and reliability engineering practices.
  • Deep Spark performance tuning skills, with experience diagnosing bottlenecks and optimizing jobs for scalability, cost, and runtime efficiency.
  • Strong programming proficiency in Python and/or Java for data processing, platform tooling, and automation.
  • Strong SQL and analytics data modeling expertise, including dimensional/star schema design and Lakehouse best practices.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (coding, code review, test acceleration, troubleshooting), including setting team expectations and validation standards for correctness, performance, and security of AI outputs.
  • Strong responsible-AI and security-first engineering mindset, including data sensitivity awareness, secure handling of inputs/outputs, roles/instance profiles, secrets management, encryption at rest/in transit, network controls, and adherence to resiliency and security expectations; experience coaching teams on safe, compliant adoption within delivery practices.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
    Preferred qualifications, capabilities, and skills
  • Experience with Delta Live Tables and advanced governance (catalogs, grants, auditing) in Databricks.
  • AWS networking knowledge (VPC, subnets, routing, security groups) and data egress controls.
  • Experience with Terraform for Infra deployments
  • Cost optimization experience: autoscaling strategies, spot vs on-demand, auto-termination, storage layouts and compaction.
  • Familiarity with Airflow, Genie, Streamlit and React
  • Observability for data systems (freshness/completeness metrics, lineage, SLAs, alerting).
  • Demonstrated leadership in code quality, reviews, testing strategy, CI/CD, and technical mentorship; excellent communication with stakeholders.
     

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.