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Senior Dataops Engineer Jobs in Indiana (NOW HIRING)

Senior Manager Data Architecture

Columbus, IN · On-site

$62.50 - $83.75/hr

Sr. Manager, Data Architecture About Circle K Circle K is a global leader in convenience and fuel ... Partner with Data Engineering, BI, Analytics, Platform, DevOps/DataOps, Data Governance, and ...

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 Indiana? The most popular types of Dataops Engineer jobs in Indiana are:
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Sr. Data Platform Engineer

Sr. Data Platform Engineer

PeopleSuite Talent Solutions

Indianapolis, IN • On-site

$150K - $180K/yr

Full-time

Posted 15 days ago


Job description

Scope of Position


Our Client is seeking a Senior Data Platform Engineer to serve as the technical authority for our Operational Data Hub within the Global Data & Analytics team. In this role, you will architect and lead the design, implementation, and optimization of enterprise-scale data ingestion, transformation, and integration solutions that power critical business operations.


As a senior technical contributor, you will own the Data Hub architecture, establish engineering standards, and drive innovation across our data platform ecosystem. You'll work closely with Data Architects, Lead Engineers, and business stakeholders to deliver scalable, reliable, and high-performing data solutions while mentoring fellow engineers and influencing technical strategy.


This role is ideal for a hands-on data engineering leader who enjoys solving complex technical challenges, shaping platform direction, and building modern cloud-based data capabilities.


Responsibilities


Data Platform Architecture & Engineering

  • Own the architecture, design, and evolution of the Operational Data Hub and its supporting processes.
  • Design and implement scalable data ingestion, transformation, orchestration, and transmission frameworks.
  • Establish technical standards, best practices, and reusable patterns for pipeline development, monitoring, error handling, and operational excellence.
  • Architect and optimize event-driven, real-time, and batch data processing solutions.
  • Lead technical design reviews and make key architectural decisions related to integrations, processing frameworks, and platform capabilities.
  • Evaluate emerging technologies and recommend innovative solutions to enhance platform performance and scalability.

Enterprise Data & Integration

  • Partner closely with Data Architects to align platform capabilities with enterprise data models and business requirements.
  • Provide technical expertise on data structures, processing efficiency, transformation complexity, and integration strategies.
  • Design and implement robust integrations across ERP systems, APIs, and enterprise applications.
  • Build advanced data transformation and enrichment capabilities that support enterprise analytics and operational workflows.

Reliability, Governance & Optimization

  • Establish data quality, validation, testing, and monitoring frameworks to ensure trusted and reliable data.
  • Implement governance, security, compliance, and operational controls across data processing workflows.
  • Drive platform performance tuning, scalability improvements, and cloud cost optimization initiatives.
  • Lead production support efforts, including incident resolution, root cause analysis, and post-incident reviews.
  • Develop comprehensive technical documentation, architecture guides, operational runbooks, and knowledge resources.

Leadership & Mentorship

  • Serve as the go-to technical expert for Data Hub architecture and engineering practices.
  • Mentor and guide Data Platform Engineers on architecture, development standards, and operational best practices.
  • Collaborate across engineering, architecture, and business teams to drive successful delivery of strategic initiatives.
  • Influence technical direction through thought leadership, knowledge sharing, and continuous improvement.


Qualifications


Required Experience

  • 5+ years of experience designing and delivering enterprise data platforms, data hubs, or large-scale data processing solutions.
  • Proven expertise building and owning modern data pipeline architectures, including real-time, event-driven, and batch processing patterns.
  • Deep experience with cloud-native data solutions, preferably within the Microsoft Azure ecosystem.
  • Advanced experience designing and optimizing Azure SQL Database or similar relational data platforms.
  • Strong expertise in Azure Function Apps, serverless computing, or comparable cloud-based processing frameworks.
  • Expert-level SQL skills with a demonstrated ability to optimize performance and support data modeling initiatives.
  • Experience integrating data across ERP systems, APIs, and enterprise applications.
  • Strong understanding of enterprise data architecture principles and modern data platform design.
  • Experience implementing CI/CD pipelines, Infrastructure as Code (IaC), and automated deployment practices.
  • Proven success troubleshooting complex production issues and improving platform reliability and performance.
  • Experience implementing security, governance, compliance, and operational controls within enterprise data environments.

Preferred Qualifications

  • Experience with Azure Data Lake, Azure Synapse Analytics, or similar modern data platform technologies.
  • Knowledge of DataOps, DevOps, observability, monitoring, and operational excellence practices.
  • Experience optimizing cloud infrastructure and managing data platform costs at scale.
  • Prior experience mentoring engineers and leading technical initiatives across cross-functional teams.

Education

  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.