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Senior Dataops Engineer Jobs in Delaware (NOW HIRING)

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Senior Dataops Engineer information

What is a senior DataOps engineer?

Senior DataOps Engineers are experienced professionals who design, implement, and manage data pipelines and workflows to ensure reliable, efficient, and scalable data operations within an organization. They bridge the gap between data engineering, DevOps, and analytics by automating data integration, deployment, and monitoring processes. Their role often includes optimizing data infrastructure, ensuring data quality, and enabling data teams to quickly deliver insights. Senior DataOps Engineers also mentor junior team members and help define best practices for data operations.

What are some common challenges a senior DataOps engineer faces when scaling data infrastructure for a growing organization?

A Senior DataOps Engineer often encounters challenges such as ensuring data pipeline reliability during rapid scaling, managing increasing data volume and complexity, and maintaining high data quality across distributed environments. Balancing automation with flexibility, integrating new tools with legacy systems, and coordinating with cross-functional teams (like data scientists and DevOps) are also key hurdles. Success in this role requires proactively identifying bottlenecks, optimizing workflows, and fostering a culture of collaboration to support evolving business needs.

What are the key skills and qualifications needed to thrive as a senior DataOps engineer, and why are they important?

To thrive as a Senior DataOps Engineer, you need a solid background in data engineering, automation, CI/CD pipelines, and strong knowledge of data architecture, usually supported by a degree in computer science or a related field. Expertise in tools like Apache Airflow, Kubernetes, Docker, cloud platforms (AWS, Azure, or GCP), and proficiency with scripting languages such as Python or Bash are typically required, along with certifications like AWS Certified Solutions Architect or Google Cloud Data Engineer. Outstanding problem-solving skills, collaboration, and effective communication are essential soft skills for integrating diverse teams and managing complex workflows. These capabilities ensure data reliability, streamlined operations, and scalable solutions in dynamic data-driven environments.

What is the difference between Senior Dataops Engineer vs Data Engineer?

AspectSenior Dataops EngineerData Engineer
CredentialsTypically requires experience with cloud platforms, scripting, and data pipeline toolsRequires knowledge of database systems, SQL, and data modeling
Work EnvironmentFocuses on deployment, automation, and maintaining data infrastructureDesigns and builds data pipelines and storage solutions
Industry UsageCommon in organizations emphasizing data operations and automationWidespread across industries for data storage and processing

The main difference is that Senior Dataops Engineers focus on managing and automating data workflows and infrastructure, while Data Engineers primarily design and build data pipelines and storage systems. Both roles require strong technical skills, but their focus areas differ within the data ecosystem.

What are popular job titles related to Senior Dataops Engineer jobs in Delaware?

For Senior Dataops Engineer jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Senior Dataops Engineer jobs in Delaware look for?

The top searched job categories for Senior Dataops Engineer jobs in Delaware are:

Senior Dataops Engineer jobs near you

Senior Data Scientist

Corporation Service Company

Wilmington, DE • On-site

$110 - $150/hr

Other

Posted 9 days ago

Corporation Service Company rating

8.3

Company rating: 8.3 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

79th of 495 rated business services

Job description

Business Intelligence Senior Data Scientist

Wilmington - HQ, USA

Monday-Friday 8:00 am to 5:00 pm

Hybrid

A Business Intelligence Senior Data Scientist develops advanced analytics and machine learning models, and maintains efficient data pipelines, reporting systems, DataOps practices for CI/CD of pipelines and BI infrastructure. Collaborate with analysts and business partners to deliver scalable solutions that support analytics, reporting, and data-driven decision making. 5+ years of experience in data engineering, BI development, or analytics engineering.

Some of the things you will be doing:
  • Implement data integration solutions for various data sources, ensuring data accuracy, consistency and completeness
  • Develop data quality, reconciliation and error handling frameworks to ensure data integrity
  • Optimize SQL and data transformation logic for performance and scalability
  • Document data flows, transformations and dependencies
  • Drive best practices in coding, testing and identify opportunities to improve processes and system reliability
  • Collaborate with business stakeholders to understand data requirements and translate them to scalable solutions.
  • Support analysts and business teams by delivering clean, structured datasets ready for visualization
  • Build predictive and statistical models to support forecasting, segmentation, and optimization
  • Implement Machine Learning and AI into Business Intelligence processes
  • Validate, test, and refine models to ensure accuracy and business relevance.
  • Analyze large, complex datasets to identify trends, patterns, and business opportunities
  • Support deployment and operationalization of analytics and data science outputs into Business Intelligence solutions
  • Understanding and knowledge of metadata management and data logs
What technical skills, experience and qualifications do you need?
  • Bachelor's degree
  • 5+ years of work experience
  • Experience supporting enterprise BI Platform & Predictive analytics
  • Experience in database technologies Oracle and Microsoft SQL
  • Extensive experience with R & Python and data modeling concepts
  • Understanding of data pipeline and ETL/ELT technologies
  • Understanding of next-gen technologies (Databricks, Snowflake, Microsoft fabric).
  • Proven experience in SQL performance tuning and recommend improvements for automation and maintainability.
  • Excellent understanding of data visualization concepts to support dashboards and reports
  • Ability to work both independently and in a team-oriented, collaborative environment
  • Strong problem solving and analytical thinking skills
  • Flexible and adaptable with respect to learning and understanding new technologies
  • Ability to effectively prioritize and execute tasks in a high-pressure environment
  • Excellent communication and interpersonal skills
  • Detail-oriented with a focus on quality and accuracy
  • Experience working in Agile/Scrum environments, participating in sprint planning, standups, reviews and retrospectives
  • Preferred - Experience working with cloud platforms such as Azure or AWS
  • Preferred - Experience in Alteryx is an added advantage

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What Corporation Service Company employees say

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