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Databricks Software Jobs in Niles, IL (NOW HIRING)

Purple Drive

Senior Data Engineer (Databricks)

Chicago, IL · Remote

$107K - $147K/yr

The ideal candidate should possess strong software engineering fundamentals and experience building ... Databricks * Apache Spark * SQL * Cloud-based ETL pipelines * CI/CD implementation * Strong ...

Deloitte

Databricks Manager

Chicago, IL · On-site +1

... software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by ... Experience with Databricks MLOps or infrastructure setup * Experience coordinating delivery teams ...

1 point system

Databricks Engineer

Chicago, IL · On-site

$118K - $141K/yr

Key Responsibilities Data Engineering & Pipeline DevelopmentDesign, develop, and maintain end-to-end data pipelines in Databricks using Spark and Delta Lake Build and optimize ELT/ETL processes for ...

Deloitte

Databricks Data Engineer

Chicago, IL

$118K - $141K/yr

As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based data engineering solutions that enable large-scale transformation. You will work with business and ...

Multivision Inc-IL

Databricks solution architect

Chicago, IL

$65 - $85.50/hr

... software Provide guidance and direction to Finance development teams on adoption of the new data ... Databricks • Apache Kafka • Terraform Enterprise • Ansible • Oracle Database • Azure SQL ...

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All JobsDatabricks Software JobsDatabricks Software Jobs in Niles, IL

Databricks Software information

See Niles, IL salary details

$47.8K

$111.3K

$165.2K

How much do databricks software jobs pay per year?

As of Jun 14, 2026, the average yearly pay for databricks software in Niles, IL is $111,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,600.00 and $129,400.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior software engineers, especially those working in high-demand fields like data engineering or cloud engineering at top tech companies, can earn $500,000 or more annually through base salary, bonuses, and stock options. Expertise in platforms like Databricks, strong coding skills, and experience in scalable data solutions are often required for such compensation levels.

What is Databricks Software?

Databricks Software is a unified analytics platform built on Apache Spark that provides tools for big data processing, machine learning, and collaborative data science. It enables organizations to store, manage, and analyze large datasets efficiently, supporting both batch and streaming data workloads. Databricks also offers collaborative notebooks, automated workflows, and integrations with cloud storage and data lakes, making it a popular choice for data engineering, data science, and business analytics teams.

Is Databricks a high paying company?

As a company specializing in data analytics and cloud-based platforms, Databricks is known to offer competitive salaries for software roles, often above industry averages, especially for positions requiring skills in Spark, Python, and cloud services. Compensation can vary based on experience, location, and role level, but overall, it is considered a high-paying employer in the tech industry.

How much do Databricks employees make?

Salaries for Databricks software roles vary based on experience, location, and specific position, but the average annual salary for software engineers at Databricks typically ranges from $100,000 to $150,000. Compensation may also include bonuses, stock options, and benefits. Entry-level roles tend to start lower, while senior positions and specialized skills can command higher pay.

What are some common challenges faced by Databricks Software Engineers, and how can they be overcome?

Databricks Software Engineers often encounter challenges related to scaling big data pipelines, optimizing Spark workloads, and integrating diverse data sources. Navigating the complexity of distributed systems and managing cloud infrastructure can be demanding, especially when ensuring data reliability and security. To overcome these challenges, engineers typically collaborate closely with data scientists, DevOps, and platform teams, leverage Databricks' extensive documentation and community support, and adopt best practices such as version control and continuous integration. Regular knowledge sharing and staying updated with new features also help engineers succeed in this dynamic environment.

What are the key skills and qualifications needed to thrive as a Databricks Software Engineer, and why are they important?

To thrive as a Databricks Software Engineer, you need strong programming skills in languages like Python, Scala, or Java, as well as a solid understanding of distributed computing and data engineering concepts. Familiarity with Databricks platform, Apache Spark, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly valued. Excellent problem-solving abilities, collaboration, and effective communication are important soft skills for this role. These skills ensure efficient development, deployment, and optimization of big data solutions that drive business insights and innovation.

What exactly are Databricks jobs?

Databricks jobs are automated tasks or workflows scheduled within the Databricks platform to run data processing, analytics, or machine learning tasks. They typically involve configuring job parameters, dependencies, and schedules using the Databricks workspace or APIs to ensure efficient data pipeline execution.

What is the difference between Databricks Software vs Data Engineer?

AspectDatabricks SoftwareData Engineer
Primary RolePlatform for data analytics and machine learningBuilds, maintains data pipelines and infrastructure
Required SkillsSQL, Spark, cloud platforms, data science basicsSQL, ETL, programming (Python, Scala), database management
Work EnvironmentCloud-based, collaborative data platformData teams, cloud or on-premises environments
CertificationsDatabricks certifications, cloud certificationsNone specific, often cloud or data certifications

While Databricks Software provides a platform for data analytics and machine learning, Data Engineers focus on building and maintaining data pipelines and infrastructure. Both roles often work together but have distinct responsibilities and skill sets within the data ecosystem.

What cities near Niles, IL are hiring for Databricks Software jobs? Cities near Niles, IL with the most Databricks Software job openings:
Databricks Software jobs near you
Infographic showing various Databricks Software job openings in Niles, IL as of June 2026, with employment types broken down into 92% Full Time, and 8% Part Time. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $111,321 per year, or $53.5 per hour.

AI Applied Architect (.NET & Databricks)

Symhas

Chicago, IL • On-site

Other

Posted 10 days ago

Job description

About the role

We're looking for a seasoned AI Applied Architect with deep .NET expertise and hands-on Databricks experience to lead the design and delivery of enterprise-grade AI and data intelligence systems. You'll sit at the intersection of software architecture, applied AI, and modern data engineering — shaping how we build, scale, and govern intelligent applications across our product portfolio. This is a high-impact role with visibility at the executive level and meaningful influence over our long-term technology roadmap.

What you'll do
  • Architect and deliver end-to-end AI/ML solutions on the .NET ecosystem, including integration with Azure AI, OpenAI, and Semantic Kernel.
  • Design and own enterprise-scale Databricks lakehouse architectures — including Medallion (bronze/silver/gold) pipelines, Delta Lake, Unity Catalog governance, and MLflow-based model lifecycle management.
  • Lead technical design sessions, define architecture standards, and drive decision-making for AI-powered product features.
  • Collaborate with product managers, data scientists, and engineering teams to translate business requirements into scalable AI and data architectures.
  • Evaluate and recommend frameworks, tools, and cloud services for AI workloads — model serving, RAG pipelines, vector stores, agents, and feature engineering on Databricks.
  • Build and govern feature engineering pipelines on Databricks, feeding production ML models and LLM-grounded retrieval systems.
  • Establish and enforce best practices for AI system reliability, security, observability, and responsible AI governance.
  • Mentor senior engineers and provide technical leadership across multiple squads.
  • Stay current on emerging AI/LLM capabilities and proactively identify opportunities for adoption.
What you bring
  • 8+ years of software engineering experience, with at least 3 years in a solutions or enterprise architect role.
  • Strong command of C# / .NET (Core / .NET 6/7/8) and cloud-native patterns on Azure.
  • Hands-on experience designing and deploying AI/ML systems in production — LLMs, RAG, embeddings, fine-tuning, or agentic architectures.
  • Proficiency with Azure OpenAI Service, Azure AI Studio, Semantic Kernel, and/or LangChain equivalents in .NET.
  • Production-grade Databricks experience: Delta Lake, PySpark/SQL, Databricks Workflows, Medallion architecture, Unity Catalog, and MLflow on Databricks.
  • Deep familiarity with microservices, event-driven design, API design, and distributed systems.
  • Proven track record leading cross-functional teams and driving large-scale technology initiatives.
  • Excellent communication skills — able to translate complex technical concepts for executive and non-technical audiences.
Nice to have
  • Experience with MLOps tooling beyond MLflow: Azure ML, Kubeflow, or Databricks Model Serving endpoints.
  • Familiarity with vector databases (Pinecone, Qdrant, Azure AI Search).
  • Background in regulated industries (fintech, healthcare, legal).
  • Experience integrating Databricks Feature Store with real-time inference pipelines.
  • Contributions to open-source AI/ML or data engineering projects.
Tech stack Category Technologies Backend .NET 8 / C#, ASP.NET Core, gRPC, REST APIs AI / LLM Azure OpenAI, Semantic Kernel, Azure AI Studio Data Platform Databricks (Delta Lake, MLflow, Unity Catalog, Workflows) Cloud & Infra Azure Kubernetes Service, Azure Data Factory, Azure Service Bus Vector & Search Azure AI Search, Pinecone, Qdrant, FAISS Databases SQL Server, Azure Cosmos DB, PostgreSQL DevOps GitHub Actions CI/CD, Docker, Kubernetes, Terraform Observability Azure Monitor, Prometheus, Grafana, MLflow tracking
Why this role is different

Most AI architect roles live either in the data platform world or the application/LLM world. This role owns both — you'll design the Databricks pipelines that prepare, govern, and serve data, and you'll architect the .NET AI systems that consume it. If you're energized by closing the gap between data engineering and applied AI delivery, this is built for you.