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Overnight Databricks Data Engineer Jobs in Milwaukee, WI

... Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in defining data governance frameworks - Understanding of modern cloud data ...

... Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $99,000 - $232,000. Actual compensation within the ...

Infrastructure Data Analytics Engineer

Brookfield, WI · On-site

$108K - $130K/yr

Experience with Azure, AWS, Databricks, Snowflake, or enterprise data platforms. * Knowledge of ... Technical Skills Programming & Analytics * SQL (Advanced) * Python * Alteryx * Power BI * Excel ...

... Databricks Certified Data Engineer/Data Analyst/ML - Proven leadership in data-driven strategies - Demonstrating thought leadership in data governance - Collaborating on strategy and transformation ...

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Data & Integration Manager

Brookfield, WI · On-site

$150K - $175K/yr

Hands-on and/or leadership experience with Power BI, Power Apps, Power Automate, Databricks, SQL ... Bachelor's degree in Information Technology, Computer Science, Data Engineering, Information ...

Senior Platform & Analytics Analyst

Waukesha, WI · On-site

$86K - $108K/yr

... Databricks, ensuring data integrity, scalability, security, and effective ETL processes. * Collaboration with cross-functional teams in manufacturing, Engineering ops, Marketing & sales involves ...

Collaborate with Data Engineering, Database, and Architecture teams to architect, develop, and ... Experience with modern data platforms such as Databricks, Snowflake, Azure Synapse, or similar ...

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

Data Architect

Mequon, WI · On-site

$56.50 - $72.75/hr

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related ... Experience with Azure Data Services, Snowflake, Databricks, PySpark, SQL, Python, Tableau, Power BI ...

Data Architect

Mequon, WI · On-site

$120 - $180/hr

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related ... Experience with Azure Data Services, Snowflake, Databricks, PySpark, SQL, Python, Tableau, Power BI ...

Data Architect

Milwaukee, WI · On-site

$62.75 - $80.75/hr

You'll work with a high-performance engineering team and report directly to the Practice Manager ... ADLS, Databricks, Fabric, Synapse, and related tooling * Define and document reference ...

Data Architect

Milwaukee, WI · On-site

$62.75 - $80.75/hr

You'll work with a high-performance engineering team and report directly to the Practice Manager ... ADLS, Databricks, Fabric, Synapse, and related tooling * Define and document reference ...

Showing results 21-40

Overnight Databricks Data Engineer information

What is an overnight Databricks data engineer?

An Overnight Databricks Data Engineer is a professional who works primarily during night shifts to manage, design, and maintain big data pipelines and workflows using Databricks, a cloud-based data analytics platform. Their responsibilities often include developing and optimizing data processing jobs, ensuring data quality, and troubleshooting issues that arise during overnight data operations. This role is critical for organizations that require 24/7 data processing, continuous ETL jobs, or real-time analytics. Working overnight may also involve monitoring automated systems, performing scheduled data loads, and collaborating with global teams to ensure data availability and reliability.

What skills and qualifications are needed to thrive as an overnight Databricks data engineer?

To thrive as an Overnight Databricks Data Engineer, you need strong proficiency in data engineering, Python or Scala programming, and experience with big data technologies, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and certifications like Databricks Certified Data Engineer are highly valued. Attention to detail, problem-solving, and effective communication are essential soft skills, especially for troubleshooting and collaborating across shifts. These competencies ensure reliable data pipeline management and efficient resolution of issues during off-hours, maintaining seamless business operations.

What unique challenges do overnight Databricks data engineers face, and how can they be addressed?

Overnight Databricks Data Engineers often work with limited real-time support, which can present challenges when troubleshooting urgent data pipeline issues or system outages. To address this, it’s essential to develop strong problem-solving skills, document processes thoroughly, and leverage automated monitoring and alerting tools. Additionally, close collaboration with daytime teams during handoff periods ensures continuity and minimizes disruptions. Building a habit of proactive communication and maintaining detailed logs helps the entire team resolve issues efficiently and maintain data quality.

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

AspectOvernight Databricks Data Engineer
Work EnvironmentPrimarily remote or on-site, working overnight shifts to support global data operations
CertificationsDatabricks certifications, cloud platform credentials (AWS, Azure), data engineering certifications
Tools & TechnologiesDatabricks platform, Spark, cloud services, SQL, Python, ETL tools
Industry UsageTech, finance, healthcare, retail with 24/7 data needs

While both roles focus on data engineering, the Overnight Databricks Data Engineer specializes in managing data pipelines on the Databricks platform during overnight shifts, often supporting global operations. A Data Engineer may work across various platforms and shifts, with broader responsibilities in data architecture and pipeline development. The overnight role emphasizes specific platform expertise and shift timing, catering to organizations with continuous data processing needs.

What are the most commonly searched types of Databricks Data Engineer jobs in Milwaukee, WI?

The most popular types of Databricks Data Engineer jobs in Milwaukee, WI are:

Data Software Engineer III - ML Ops

Northwestern Mutual Life Insurance Company

Milwaukee, WI • On-site

$112K - $135K/yr

Full-time

Posted 7 days ago


Key responsibilities

  • Build and standardize services, data pipelines, automation, and dashboards for the ML Ops platform.

  • Develop reliable data pipelines to transform and aggregate data from source systems and data platforms.

  • Collaborate with data scientists, software engineers, and infrastructure teams to enable automation, monitoring, and deployment of machine learning models.


Northwestern Mutual rating

8.0

Company rating: 8.0 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

171st of 315 rated insurance


Job description

This is a hybrid position. 3 days onsite at our downtown Milwaukee Corporate Office.
Northwestern Mutual (NM) has been helping people and businesses achieve financial security for over 169 years. Through a distinctive, whole-picture planning approach including both insurance and investments, we empower people to be financially confident. We combine the expertise of our financial professionals with a personalized digital experience and groundbreaking technology to best serve our clients.
About the Job
Data is a critical driver of this approach and a cornerstone for how we engage with our customers. To help lead the effort, NM's Assistant Director, Data Software Engineering - AI/ML Ops is seeking a highly motivated, curious, and passionate software engineers to build and design services, data pipelines, automation, and dashboards for our ML Ops platform and to implement and standardize practices for traditional and generative artificial intelligence.
You will be joining our Data Solutions and Enablement department (DSE) whose mission is to unlock and provide analytical insight on our core customer and client data to better serve our customers, field representative, and business partners. As a part of the team you will collaborate with Data Scientists, Software Engineers, Data Engineers, and Product Owners throughout the organization to help unlock the value of data through predictive analytics, operationalized machine learning, applied AI and generative AI.
What You'll do
ML Ops Team responsibilities include but are not limited to:
  • Building and standardizing services and patterns in Python and Java to enable model deployment, training, inference, and monitoring.
  • Building services and automation to streamline and manage the stages of the AI/ML life cycle and model governance
  • Develop reliable data pipelines that transform and aggregate data from NM's source systems and data platforms
  • Establish and maintain NM's data science, ML and AI platforms, with a focus on rapid iteration and operational deployment of predictive models, and cost management of workloads
  • Integrating various ML Ops platforms together such as Databricks, AWS Sagemaker, AWS Bedrock.
  • Establish a feature store of curated metrics, attributes, and features for ML models
  • Collaborate closely with data scientists, DevOps Engineers, and enterprise infrastructure teams to enable automation and monitoring across the machine learning lifecycle
  • Develop ML model monitoring pipelines for model performance, data quality, and gen AI evaluation, tracing, and metrics.

AI/ML Ops Baseline Competencies:
  • We work in Python and Java, leveraging Spring, Flask, FastMCP, FastMCP, Pandas, Spark, LangGraph and ML Flow
  • We leverage AWS and Databricks often and deploy software and AI/ML solutions CI/CD first. We aspire to automate and standardize everything.
  • We expect proficiency with databases and SQL from RDBMS (Postgres, SQL Server, MySql etc.) or big data platforms (Databricks, Spark, Redshift, Snowflake, Big Query etc).
  • We expect familiarity and experience with basic ML algorithms, LLMs, and GenAI/Agentic concepts.
  • We expect an understanding of basic tools and libraries common to data science, AI and ML. e.g. ML Flow, Pandas/Numpy/Sklearn, PyTorch/TensorFlow, or LlamaIndex/LangChain/LangGraph OR a strong mathematical and computer science background.
  • We are passionate about continuous learning and problem solving. Curiosity is expected, welcome, and rewarded.
  • We collaborate and work creatively every day.

The Data Software Engineer III leads the design and implementation of complex data systems, leveraging advanced data engineering techniques and emerging leadership skills.
Primary Duties & Responsibilities
  • Architect and develop scalable data pipelines using advanced programming skills
  • Gather and translate data requirements into technical solutions
  • Optimize sophisticated data integration and transformation processes
  • Enhance existing systems for performance and scalability
  • Mentor junior engineers and oversee CI/CD pipelines

What You'll Bring to the Role
  • Bachelor's degree in Computer Science, Engineering, or equivalent experience
  • Strong expertise in programming languages for data engineering
  • Experience with data processing frameworks and Kubernetes
  • Proficiency with cloud platforms (e.g., AWS, Azure, Google Cloud) and data visualization tools
  • Understanding of machine learning concepts
  • Expertise in CI/CD processes and version control
  • Expertise in source code management using Git and GitFlow
  • Strong understanding of CI/CD processes and tools (e.g., Jenkins, GitLab CI/CD, CircleCI) and experience with artifact repositories (e.g., Nexus, Artifactory)
  • Strong understanding of agile methodologies and experience in an agile development environment

Skills You Have
Adaptive Communication (NM) - Formulates strategies to be used to convey complex information about services, products, systems, or processes to targeted audiences; communicates and liaises between technical and non-technical audiences.
Analytical Thinking (NM) - Organizes and compares various aspects of a situation to comprehend and identify key or underlying complex issues through the use of quantitative data and analysis; leverages strong business acumen, problem solving, and interpersonal skills to think critically about situations from multiple perspectives and consistently seeks ways to improve processes.
Consulting (NM) - Connects with stakeholders to understand and gain specific information to help resolve customer problems in a given domain. Communicates effectively intent to customers, solicits customer requirements, utilizes domain knowledge and collaborates with the right stakeholders.
Databases & Data Platforms (NM) - Utilizes knowledge of databases to access, manage, and update information, typically containing aggregations of data records or files; includes understanding of different types of databases.
Engineering Expertise & Practices (NM) - Applies specialized experiences in different facets of engineering, including data, applications, cyber, systems, operations, product, security, and testing, along with technical aptitude to adapt new expertise as they become relevant through an understanding of underlying engineering principles.
Machine Learning (NM) - Applies understanding of and/or computes large data structures and sets using quantitative analysis methods, while building out data pipelines and statistics.
Programming Languages (NM) - Demonstrates proficiency in one or more programming languages to execute activities, tasks, practices, and deliverables associated with writing and modifying programs and scripts that comprise an application system; designs, codes, tests, and installs complex computer programs and maintains detailed documentation of programming tasks.
#LI-Hybrid
Compensation Range:
Pay Range - Start:
$108,160.00
Pay Range - End:
$162,240.00
Geographic Specific Pay Structure:
Structure 110:
Structure 115:
We believe in fairness and transparency. It's why we share the salary range for most of our roles. However, final salaries are based on a number of factors, including the skills and experience of the candidate; the current market; location of the candidate; and other factors uncovered in the hiring process. The standard pay structure is listed but if you're living in California, New York City or other eligible location, geographic specific pay structures, compensation and benefits could be applicable, click here to learn more.
Grow your career with a best-in-class company that puts our clients' interests at the center of all we do. Get started now!
Northwestern Mutual is an equal opportunity employer that welcomes talented individuals of all backgrounds. We are committed to creating and maintaining an environment in which each employee can contribute creative ideas, seek challenges, assume leadership and continue to focus on meeting and exceeding business and personal objectives.

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About Northwestern Mutual

Sourced by ZipRecruiter

Northwestern Mutual has been helping families and businesses achieve financial security for over 160 years through a distinctive planning approach that integrates risk management with wealth accumulation, preservation, and distribution. With more than $290 billion in assets, $30 billion in revenues and more than $1.9 trillion worth of life insurance protection in force, Northwestern Mutual delivers financial security to more than 4.6 million clients. People are the power behind Northwestern Mutual, and diversity makes us better. We are committed to reflecting and serving the marketplace. We do so by attracting and improving the engagement of those who bring their outstanding perspectives, ideas, and beliefs.

Industry

Finance and insurance

Company size

5,001 - 10,000 Employees

Headquarters location

Milwaukee, WI, US