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Senior Dataops Engineer Jobs in Florida (NOW HIRING)

VaxCare

Data Engineer

Orlando, FL · On-site

$106K - $128K/yr

... senior technical contributor. RESPONSIBILITIES * Develop and maintain Delta Lake-based data ... Follow DataOps best practices including testing strategies, performance tuning, and data platform ...

Kimley-Horn

Senior Data Engineer

Jacksonville, FL · On-site

$92K - $126K/yr

Kimley-Horn is seeking a Senior Data Engineer to join our Innovations team in Jacksonville, Florida ... DataOps practices. What We're Looking For * 5+ years of experience in data engineering, analytics ...

Kimley-Horn

Senior Data Engineer

Jacksonville, FL · On-site

$98K - $133K/yr

Overview Kimley-Horn is seeking a Senior Data Engineer to join our Innovations team in Jacksonville ... DataOps practices. Qualifications What We're Looking For * 5+ years of experience in data ...

Kimley-Horn

Senior Data Engineer

Jacksonville, FL · On-site

$92K - $126K/yr

Overview Kimley-Horn is seeking a Senior Data Engineer to join our Innovations team in Jacksonville ... DataOps practices. Qualifications What We're Looking For * 5+ years of experience in data ...

Kimley-Horn

Senior Data Engineer

Jacksonville, FL · On-site

$98K - $133K/yr

Overview Kimley-Horn is seeking a Senior Data Engineer to join our Innovations team in Jacksonville ... DataOps practices. Qualifications What We're Looking For * 5+ years of experience in data ...

Kimley-Horn

Senior Data Engineer

Jacksonville, FL · On-site

$98K - $133K/yr

Overview Kimley-Horn is seeking a Senior Data Engineer to join our Innovations team in Jacksonville ... DataOps practices. Qualifications What We're Looking For * 5+ years of experience in data ...

Matia

About Matia Matia (matia.io) is at the forefront of the DataOps revolution , building a unified ... Identify, target, and engage potential customers in the data and engineering space, through cold ...

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Senior Dataops Engineer information

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 Senior DataOps Engineers?

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 the most commonly searched types of Dataops Engineer jobs in Florida? The most popular types of Dataops Engineer jobs in Florida are:
What are popular job titles related to Senior Dataops Engineer jobs in Florida? For Senior Dataops Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Senior Dataops Engineer jobs in Florida look for? The top searched job categories for Senior Dataops Engineer jobs in Florida are:
What cities in Florida are hiring for Senior Dataops Engineer jobs? Cities in Florida with the most Senior Dataops Engineer job openings:
Senior Dataops Engineer jobs near you
Sr Platform Data Engineer.- SGWS

Sr Platform Data Engineer.- SGWS

ShiftCode Analytics

Hollywood, FL • Hybrid

$104K - $125K/yr

Other

Posted 6 days ago

Job description

Sr. Data Platform Engineer

We're looking for a Sr. Data Platform Engineer who thrives in a hybrid role—60% administration and 40% development/support—to help us scale our data and DataOps infrastructure. You'll work with cutting-edge technologies like Databricks, Apache Spark, Delta Lake, and AWS CloudOps, Cloud Security, while supporting mission-critical data pipelines and integrations. If you're a hands-on engineer with strong Python skills, deep AWS experience, and a knack for solving complex data challenges, we want to hear from you.

Responsibilities:

  • Design, develop, and maintain scalable ETL pipelines and integration frameworks.
  • Administer and optimize Databricks and Apache Spark environments for data engineering workloads.
  • Build and manage data workflows using AWS services such as Lambda, Glue, Redshift, SageMaker, and S3.
  • Support and troubleshoot DataOps pipelines, ensuring reliability and performance across environments.
  • Automate platform operations using Python, PySpark, and infrastructure-as-code tools.
  • Collaborate with cross-functional teams to support data ingestion, transformation, and deployment.
  • Provide technical leadership and mentorship to junior developers and third-party teams.
  • Create and maintain technical documentation and training materials.
  • Troubleshoot recurring issues and implement long-term resolutions.

Requirements:

  • Bachelor's or Master's degree in Computer Science or related field.
  • 5+ years of experience in data engineering or platform administration.
  • 3+ years of experience in integration framework development with a strong emphasis on Databricks, AWS, and ETL.
  • Strong AWS: fundamental understanding of cloud trail, cloud watch, S3, and ML platform experience (Glue, Lambda, AWS console management)
  • Experience managing Databricks on AWS platform and integrating with Redshift and Databricks
  • Strong programming skills in Python and PySpark.
  • Expertise in Databricks, Apache Spark, and Delta Lake.
  • Proficiency in AWS CloudOps, Cloud Security, including configuration, deployment, and monitoring.
  • Strong SQL skills and hands-on experience with Amazon Redshift.
  • Experience with ETL development, data transformation, and orchestration tools.
  • Kafka for real-time data streaming and integration.
  • Fivetran and DBT for data ingestion and transformation.
  • Familiarity with DataOps practices and open-source data tooling.
  • Experience with integration tools such as Apache Camel and MuleSoft.
  • Understanding of RESTful APIs, message queuing, and event-driven architectures.
ShiftCode Analytics logo

About ShiftCode Analytics

Sourced by ZipRecruiter

We specialize in solid end-to-end delivery of tailor-made technology solutions designed by the Top 1% Software Engineering teams. Our innate digital leadership identity powers transformation across every industry. We are always ready to drive meaningful change with a strategic vision for the future. We rigorously test for logical/mathematical reasoning skills, technical ability and soft skills in our interview process. Only those engineers who score highly across each of these areas are presented to our clients.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

Tampa, FL, US

Year founded

2019

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