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Software Engineer Data Analyst Jobs in Delaware (NOW HIRING)

ECCLESIASTES INC

Sr. Software Engineer

Newark, DE · On-site

$120K - $159K/yr

Analyze business user needs, design, develop and implement software applications and systems using ... Engineering, a closely related field. Foreign degree equivalent is acceptable. 5 years ...

Judge Group, Inc.

Software Engineer

Wilmington, DE · On-site

$73 - $78/hr

Software Engineer, Full Stack (Java/React) We are not accepting C2C or 1099 arrangements. Location ... Design and implement APIs, integrations, and data exchange services with internal and external ...

JPMorganChase

Lead Software Engineer

Wilmington, DE · On-site

... Software Engineer to play a crucial role in their Enterprise technology team. This position ... analysis and requirements traceability), validating outputs and handling operational data according ...

ITW Avery Weigh-Tronix

Embedded Software Engineer

DE · On-site

$131K - $172K/yr

This position requires strong analytical skills, a solid foundation in software engineering principles, and the ability to work independently across most phases of the development cycle. The ideal ...

Cisco

Software Engineer, Backend

Dover, DE · On-site

$155K - $222K/yr

... analytics, and data lakes across Cisco. We'rea small, expert team that owns this software end to ... Programming experience in Rust, Scala, Python. * Experience with observability tooling such ...

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All JobsSoftware Engineer Data Analyst JobsSoftware Engineer Data Analyst Jobs in Delaware

Software Engineer Data Analyst information

See Delaware salary details

$44.5K

$129.8K

$177.7K

How much do software engineer data analyst jobs pay per year?

As of Aug 9, 2026, the average yearly pay for software engineer data analyst in Delaware is $129,828.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,600.00 and $137,600.00 per year, depending on experience, location, and employer.

What is the difference between Software Engineer Data Analyst vs Data Scientist?

AspectSoftware Engineer Data AnalystData Scientist
Required CredentialsBachelor's in CS, Data Analysis, or related; programming skillsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentSoftware development teams, data analysis projectsResearch, modeling, predictive analytics teams
Employer & Industry UsageTech companies, finance, healthcareTech firms, research institutions, finance
Common Search & ComparisonOften compared for data roles involving coding and analysisMore focused on predictive modeling and research

The main difference between a Software Engineer Data Analyst and a Data Scientist lies in their focus and skill set. Software Engineers Data Analysts primarily develop data tools and analyze data using programming, while Data Scientists focus on building predictive models and advanced analytics. Both roles require strong technical skills, but Data Scientists typically have more expertise in statistics and machine learning.

How do software engineer data analysts typically collaborate with other teams to deliver data-driven solutions?

Software Engineer Data Analysts work closely with cross-functional teams, including data scientists, product managers, and software developers, to collect requirements and translate business needs into actionable analytics solutions. They often participate in regular meetings to align on project goals, share progress, and troubleshoot data integration challenges. Effective communication is key, as they must explain technical findings to non-technical stakeholders and ensure that the data pipelines and dashboards they develop meet end-user needs. This collaborative environment provides opportunities to broaden technical skills and gain insights into various business functions.

What are the key skills and qualifications needed to thrive as a software engineer data analyst, and why are they important?

To thrive as a Software Engineer Data Analyst, you need strong programming skills (such as Python or Java), a solid understanding of data structures and algorithms, and a background in statistics or computer science. Proficiency in SQL, data visualization tools (like Tableau or Power BI), and experience with big data platforms (such as Hadoop or Spark) are typically required, along with relevant certifications. Analytical thinking, problem-solving ability, and effective communication help you translate complex data into actionable insights. These skills ensure you can extract, analyze, and communicate data-driven solutions that support business objectives.

What is a software engineer data analyst?

A Software Engineer Data Analyst is a professional who combines software engineering skills with data analysis expertise to extract insights from data and build applications or tools for data processing. They typically design, develop, and maintain software systems that collect, store, and analyze large datasets. Their role often involves writing code to automate data workflows, create dashboards, and perform statistical analyses. These professionals work closely with other engineers, data scientists, and business stakeholders to support data-driven decision making.
What cities in Delaware are hiring for Software Engineer Data Analyst jobs? Cities in Delaware with the most Software Engineer Data Analyst job openings:
Software Engineer Data Analyst jobs near you

Lead Software Engineer - Databricks

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 2 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

73rd of 170 rated banks

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.

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