Identify friction points experienced by data engineers, data scientists, and analysts, and translate them into platform features, reusable patterns, and enablement artifacts. Work across federated ...
Quick apply

Identify friction points experienced by data engineers, data scientists, and analysts, and translate them into platform features, reusable patterns, and enablement artifacts. Work across federated ...
Quick apply
Identify friction points experienced by data engineers, data scientists, and analysts, and translate them into platform features, reusable patterns, and enablement artifacts. Work across federated ...
What are the key skills and qualifications needed to thrive as a Data Analyst, and why are they important?
What are some common challenges Data Analysts face when working with large datasets, and how are they typically addressed?
What does a Data Analyst do?
How much does an entry level data analyst make?
What jobs make $3,000 a month without a degree?
Will AI replace a data analyst?
What is the difference between Data Analyst vs Data Scientist?
| Aspect | Data Analyst | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's degree in statistics, mathematics, or related field; often certifications in data analysis tools | Bachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees |
| Work Environment | Business settings, focusing on data reporting and visualization | Research and development environments, focusing on predictive modeling and complex algorithms |
| Employer & Industry Usage | Retail, finance, healthcare, and marketing companies | Tech firms, research institutions, and large enterprises |
While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.
Do workers at Corteva Agriscience get paid breaks?
Does Corteva Agriscience pay people when they’re sick?
At Corteva Agriscience, are sick days and vacation days separate paid time off?
Is the health insurance from Corteva Agriscience affordable enough for their workers?
Do people get paid time off at Corteva Agriscience?
How far ahead of time do people find out their work schedule?
Do workers at Corteva Agriscience worry about hours?
Do Corteva Agriscience workers get to choose the shifts they work?
How easy is it for Corteva Agriscience workers to change shifts?
How easy is it to get time off at Corteva Agriscience?
Do Corteva Agriscience managers change schedules at the last minute?
Do workers at Corteva Agriscience do extra work that they don't get paid for?
How easy is it to take sick days at Corteva Agriscience?
Is working at Corteva Agriscience good if you’re a parent or caregiver?
Do people at Corteva Agriscience feel treated with respect by their managers?
Do people at Corteva Agriscience get to take their breaks without interruption?
Is it stressful to work at Corteva Agriscience?
Do people at Corteva Agriscience enjoy their jobs?
Do people at Corteva Agriscience recommend working with their team?
Do people get enough training when they start at Corteva Agriscience?
Do people get support to advance at Corteva Agriscience?
Do people think Corteva Agriscience’s headquarters understands what’s happening where they work?
Do workers feel well informed about how Corteva Agriscience is doing?

8.1
Based on 69 frontline employees who took The Breakroom Quiz
103rd of 511 rated manufacturers
Platform Staffing Group (an STA Group Company) is looking for a Sr. Principal Software Architect to assist our client in leading the development and evolution of our Data & ML Platform using Databricks as the foundational technology.
Remote - candidate can be considered remote if currently lives in the US and lives more than 50 miles from Johnston, IA location. Johnston, IA – candidate living within 50-mile radius of location required onsite T/W/TH each week.
DUTIES & RESPONSIBILITIES
This individual will lead the development and evolution of our client’s Data & ML Platform using Databricks as the foundational technology. This role focuses on building platform capabilities that enable federated domain teams across R&D to efficiently build, operate, and manage their own data and AI products. This includes working closely with data professionals to understand friction points and develop platform features, patterns, and enablement pathways that improve productivity, governance, and adoption. This work directly supports a federated data mesh strategy and is expected to grow over multiple years.
Develop and enhance Databricks-based platform capabilities to improve the productivity, governance, and autonomy of federated domain teams.
Collaborate with Data Platform and ML Platform leadership to align platform features to strategic roadmap and domain enablement needs.
Act as a technical and architectural advisor to teams onboarding to the platform, helping them apply best practices rather than building their solutions for them.
Identify friction points experienced by data engineers, data scientists, and analysts, and translate them into platform features, reusable patterns, and enablement artifacts.
Work across federated data domains to ensure platform consistency, governance alignment, and scalable adoption aligned with data mesh principles.
Provide technical leadership while still being capable of hands-on development when shaping reference implementations, IaC modules, or platform accelerators.
Advocate for secure-by-default design, applying modern security principles and working knowledge of cyber practices in a cloud-native platform context.
Contribute to FinOps-aware decision-making by communicating trade-offs between different Databricks implementation patterns (clusters vs. serverless vs. SQL warehouses, Unity Catalog configuration, etc.).
Required Skills
7+ years of technical leadership with data or platform engineering roles preferred
Experience or deep understanding of designing or enabling federated data/ML environments where teams self-serve platform capabilities.
Strong understanding of platform architecture and patterns that support data mesh or domain-oriented enablement.
Ability to think in terms of platform products including prioritizing reusable capabilities, reducing cognitive load for users, and avoiding central engineering bottlenecks.
Experience influencing architecture decisions and guiding teams through platform-aligned adoption pathways.
Knowledge of/or expertise with Databricks as a platform beyond notebook usage, including governance, workspace design, multi-domain enablement, and Unity Catalog patterns.
Nice to Have Skills
Hands-on familiarity with Terraform, AWS infrastructure concepts (IAM, S3, networking), and IaC workflows.
Platform mindset with experience building internal platform products with developer experience and scale in mind.
General knowledge of cybersecurity and secure-by-default design patterns in cloud platforms.
Awareness of FinOps principles and cost optimization patterns specific to Databricks (e.g., cluster policy trade-offs, compute model selection, multi-workspace vs multi-catalog trade-offs).
Experience working within a federated data governance or data mesh operating model.
PLATFORM STAFFING GROUP, an STA Group Company IS AN EQUAL OPPORTUNITY EMPLOYER Follow us on X @PLATSTAFFJOBS
Get the full story on Breakroom
Sourced by ZipRecruiter
Manufacturing
10,000+ Employees
Indianapolis, IN, US
2018