dataops engineer

Citylogix

<div>About Citylogix
Citylogix is a leading provider of data and analytics for smart city transportation infrastructure, leveraging LiDAR, 360&deg; imaging, and AI-powered analytics to create detailed digital maps, and provide predictive analytics for proactive asset management. 
About the role
The DataOps Engineer position is central to developing sophisticated data processing pipelines that handle diverse data formats and volumes. This role involves designing and implementing scalable ETL/ELT workflows using modern big data frameworks and orchestration tools. The engineer will create reusable components and optimize processing efficiency to meet demanding performance requirements. The position requires deep technical expertise in distributed systems and data processing patterns. The successful candidate will work at the intersection of data engineering and operations, ensuring pipelines are both functionally robust and operationally excellent. 
What you'll do<ul><li>
Implement orchestration with Airflow/Prefect</li><li>
Build reusable components and shared libraries</li><li>
Optimize processing performance and costs</li><li>
Manage schema evolution and data versioning</li><li>
Integrate diverse data sources and formats</li><li>
Create monitoring dashboards and metrics</li></ul>
Qualifications<ul><li>
3+ years building production data pipelines</li><li>
Expertise in big data frameworks (Spark, Hadoop)</li><li>
Experience with workflow orchestration tools</li><li>
Strong Python/Scala/Java programming skills</li><li>
Understanding of distributed systems</li></ul></div>

DataOps Engineer

Rrootshell Technologiiss

Python, SQL, NoSQL, Cypher, Airflow, Cloud Data Services, Data Modeling, ETL/ELT Pipelines, DataOps, Data Governance, Data Quality Management 
 Looking for candidates you can join immediately or 30 Days of notice period.

Data Engineer

EPAM Systems

<div>We are seeking a Senior Data DevOps Engineer to support and optimize our data platform within Azure environments.
You will play a key role in deploying and maintaining scalable, secure data infrastructures while collaborating with various teams to enhance data workflows and CI/CD pipelines. Your expertise with Databricks and Azure tools will be essential to ensure smooth operations and continuous improvement of our data systems. Join us to contribute your skills in a dynamic environment focused on advanced data solutions.
Responsibilities<ul><li>
Deploy and configure data platforms in Databricks according to approved architecture and solutions ensuring production readiness and scalability</li><li>
Collaborate with cross-functional teams including data engineering, machine learning, platform, and quality assurance to design and maintain CI/CD pipelines and supporting tools for data workflows</li><li>
Diagnose and resolve issues related to build and deployment pipelines, data workflows, and production workloads including performing root cause analysis and implementing preventive solutions</li><li>
Develop and standardize configuration management practices covering infrastructure configuration, environment parameters, secrets management, and cluster policies to maintain consistency</li><li>
Produce and update technical documentation such as deployment guides, operational runbooks, pipeline logic, and platform configurations</li><li>
Implement governance and security best practices for data platform environments</li><li>
Support automation efforts to promote efficient environment deployment and pipeline operations</li><li>
Participate in continuous improvement initiatives for data platform infrastructure and workflows</li></ul>
Requirements<ul><li>
Experience of 3 or more years in roles such as Build Engineer, DevOps Engineer, or Platform Engineer supporting delivery and operations</li><li>
Proficiency in Databricks, Azure Data Factory, Azure DevOps, and general Microsoft Azure environment management</li><li>
Knowledge of DataOps practices, including automated deployment of data pipelines, environment promotion, and governance</li><li>
Experience in troubleshooting and resolving pipeline and production data workflow issues</li><li>
Strong communication and collaboration capabilities to work effectively with engineering, data, and operations teams</li><li>
English language proficiency at the B2 level or higher for participation in technical discussions and documentation preparation</li><li>
Ability to produce and maintain clear technical documentation and runbooks</li></ul>
Nice to have<ul><li>
Experience with MLOps including model deployment, monitoring, and lifecycle automation for machine learning workloads</li></ul>
We offer<ul><li>
CONTINUOUS UPSKILLING, LEARNING &amp; DEVELOPMENT<ul><li>
Diversity of tasks and projects</li><li>
Assessment center for objective review of competency level</li><li>
Personal development plan</li><li>
Mentoring programs and leadership development</li><li>
Certification and professional development support</li><li>
Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses</li><li>
English courses taught by certified teachers</li></ul></li><li>
CORPORATE BENEFITS<ul><li>
Extra leave days</li><li>
Referral bonuses</li></ul></li><li>
COMPENSATION PACKAGE<ul><li>
Competitive compensation paid in USD</li><li>
Regular salary and performance reviews</li></ul></li><li>
MEDICAL &amp; HEALTHCARE<ul><li>
Private health insurance</li><li>
Well-being events</li></ul></li><li>
WORKING ENVIRONMENT<ul><li>
Recreation areas and kitchens</li><li>
Tea, coffee, and snacks</li><li>
Well-being events</li><li>
Sports equipment and game consoles</li><li>
IT Equipment</li><li>
Microsoft's Software Assurance Home Use Program (HUP)</li></ul></li></ul>
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.</div>

Senior Data DevOps Engineer with Azure

NewMind AI

<div>I - Who We Are?
New Mind AI is an innovative and pioneering company specializing in leveraging big data through a comprehensive and holistic approach. From data digitization and classification to deriving meaningful insights and extracting actionable outputs, we employ advanced taxonomies and ontologies to organize data in a structured and insightful manner, creating a semantic layer to better understand corporate data. Our mission extends beyond mere data structuring; we empower companies to transform their data into actionable insights, facilitating dynamic corporate governance.
With over 300 task-oriented and domain-specific AI models, built using an orchestration of experts framework, we provide robust solutions for dynamic corporate governance. By implementing dynamic knowledge network structures, we develop advanced AI models that ensure effective management of corporate data in the business world. Our expertise spans AI-driven business solutions, including AI legal tech products, excelling in natural language processing, deep learning, machine learning, data analysis, and data visualization.
Headquartered in YT&Uuml; Teknopark, Maslak, Istanbul, and operating four specialized laboratories&mdash;Data Visualization Lab in India, Data Taxonomy Lab in Bomonti, and Big Data and Legal Tech Labs in Maslak&mdash;we are leaders in big data analysis in T&uuml;rkiye and beyond. Our flagship dynamic knowledge management platforms, Mecellem, Malumat, and Mahfuz, empower professionals across various industries by streamlining complex tasks, optimizing decision-making, and managing business risks with precision.
Through our cutting-edge AI tools, including Generative AI, LLMs, text-to-speech and speech-to-text, image recognition, voice recognition, function call, graphRAG, OCR, blockchain and RAG, we set new standards in business technology. We deliver smarter, more dynamic solutions for the business world, both in T&uuml;rkiye and internationally. 
II - Who We Are Looking For?
We are seeking a skilled and experienced MLOps Engineer to join our team. The ideal candidate will have a strong understanding of MLOps/DataOps/AIOps/DevOps/LLMOps methodologies and principles, with expertise in building and maintaining robust MLOps infrastructure. This role requires proficiency in Python and Bash programming languages, experience with containerization technologies like Docker and Kubernetes, and familiarity with various MLOps frameworks and tools. The ideal candidate will be passionate about the engineering behind machine learning, with a strong understanding of data pipelines, model training, deployment, and monitoring. 
III - What Will Be Your Responsibilities?
(i) Design and implement scalable MLOps infrastructure, including orchestrated data pipelines, continuous model training and automated deployment systems. (ii) Develop and maintain monitoring and configuration management tools to ensure the reliability and performance of our on-premises MLOps infrastructure. (iii) Collaborate with data scientists and software engineers to build scalable and efficient data pipelines and model training and deployment systems. (iv) Install and configure hardware, operating systems, and related software for tuning computing resources. (v) Prepare development and production platforms for Machine Learning Operations with containerization technologies. (vi) Communicate with a team of data scientists, machine learning engineers, and architects to document processes and ensure smooth collaboration. (vii) Troubleshoot and debug issues related to MLOps infrastructure and deployment processes. (viii) Take offline models built by Machine Learning Engineers and turn them into real machine learning production systems. (ix) Stay up-to-date with the latest trends and technologies in MLOps, LLMOps, machine learning, and artificial intelligence. 
IV - What Is Required from You?
(i) Qualifications: Bachelor's degree in Computer Engineering, Data Science, or a related field. Master's or PhD degree is a plus. (ii) Experience: 2+ years of hands-on experience in designing and implementing MLOps solutions, including experience with containerization technologies, CI/CD pipelines, and data pipeline orchestration platforms. (iii) Expertise: Strong understanding of MLOps/DataOps/AIOps/DevOps/LLMOps methodologies and principles. Proficiency in Python and Bash programming languages. Experience with Machine Learning frameworks - like scikit-learn, LGBM, TensorFlow, PyTorch etc. Experience with MLOps Frameworks like MLFlow, Kedro, W&amp;B, DVC etc. Experience with at least one Machine Learning/Data Pipeline orchestration platform such as Apache Airflow, MageAI, Kubeflow etc. Experience with big data processing frameworks such as Apache Spark and streaming platforms like Apache Kafka. Familiarity with data formats including Parquet files and data lakehouse technologies such as Apache Hudi. Strong knowledge of containerization with Docker and container orchestration technologies, such as Docker Swarm, Kubernetes, Slurm etc. Experience with Kubernetes backup and disaster recovery tools such as Velero. (iv) Knowledge: Strong knowledge of infrastructure monitoring tools such as Prometheus, Grafana, Evidently, Zabbix etc. Experience with Configuration Management tools such as Ansible, Chef, Puppet, Terraform etc. Hands-on experience in Linux (Debian Based) and administration. Experience working with cloud computing and database systems such as Elasticsearch, MongoDB, MySQL, Postgres, Couchbase etc. Knowledge of distributed storage systems such as Ceph and object storage solutions like Minio. Understanding of GPU virtualization technologies including MIG (Multi-Instance GPU) and MPS (Multi-Process Service). Expertise on VCS systems such as Gitlab, Github etc. (v) Skills: Self-motivated, organized, proactive, and flexible. Passion for the engineering behind machine learning and scaling it. Experience with DevOps and CI/CD practices. Strong Understanding cluster based microservice infrastructures in High Availability and fault-tolerant systems. Hands-on experience on Data Migration and Version Bump Operations. Understanding Network fundamentals and configuration management, troubleshooting. Hands-on experience on Zero downtime deployment operations. Experience with reverse proxying and load balancing technologies such as Nginx, HAProxy, Traefik, Envoy etc. Ability to design and implement build MLOps pipelines on premise/cloud. Ability to understand tools used by Machine Learning Engineers and experience with software development and test automation. Experience with Agile methodologies and Scrum frameworks. Hands-on experience on Virtual Machines, including hypervisors (Hyper-V, ESXi etc.). (vi) Language: Fluent in English, both written and spoken, is required for effective communication with international teams and clients. (vii) Competencies: Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Ability to work independently and as part of a team. Passion for AI and its potential to transform businesses. 
V - Why Work at New Mind AI?
New Mind AI offers a unique opportunity for ambitious young professionals seeking to make a real impact in the rapidly growing field of AI. As a company at the forefront of AI innovation, we are driven by a strong mission to empower businesses with actionable insights derived from data. This translates to a dynamic and stimulating work environment where you will be challenged to think critically, develop your skills, and contribute to groundbreaking projects. Here are some key reasons why New Mind is an ideal place for young talent: (i) be a part of something bigger: Our work goes beyond simply developing AI models. We are shaping the future of business and helping organizations navigate the complex world of data-driven decision-making; (ii) work with leading experts: You will be surrounded by a team of passionate and knowledgeable individuals who are experts in their fields. This collaborative environment fosters continuous learning and growth; (iii) gain valuable experience: You will have the opportunity to work on diverse projects, utilizing cutting-edge AI tools and technologies, including Generative AI, LLMs, and more; (iv) make a real difference: Your contributions will directly impact our company's growth and success, contributing to the advancement of AI technology and its positive impact on the world; (v) global reach: As a company with a global presence, you will be exposed to a diverse range of perspectives and opportunities to work with clients and partners from around the world; (vi) invest in your future: New Mind is committed to supporting its employees' professional development and offers opportunities for growth within the company.</div>

MLOps Engineer

<div>EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
We are looking for a Lead MLOps Gen AI Engineer to support the development and deployment of AI tools.
This role bridges data science, engineering, and cloud infrastructure, focusing on building scalable and automated production-grade AI systems. You will work closely with data scientists, business stakeholders, and cloud engineers to convert prototypes into dependable, high-performance applications that drive predictive analytics, generative AI solutions, and interactive dashboards for business leaders. If you have substantial experience in MLOps and cloud infrastructure and enjoy collaborating across teams, we encourage you to apply.
Responsibilities<ul><li>
Collaborate with data scientists to convert ML and generative AI experiments into scalable production pipelines</li><li>
Develop and maintain shared code repositories and reusable components</li><li>
Design and implement CI/CD pipelines in AWS or Azure environments for deploying models, APIs, and generative AI tools</li><li>
Build and manage data pipelines and DataOps processes</li><li>
Containerize applications using Docker and deploy them with cloud-native services</li><li>
Automate infrastructure provisioning using Terraform and manage database schemas in Azure and Snowflake</li><li>
Deploy and administer generative AI applications such as chatbots, retrieval-augmented generation (RAG) systems, and predictive tools</li><li>
Implement monitoring, observability, and explainability solutions to ensure system stability and performance</li><li>
Establish alerting, rollback strategies, and observability frameworks to maintain operational stability</li><li>
Participate in code reviews and recommend improvements to workflows and processes</li></ul>
Requirements<ul><li>
Experience of 8 to 12 years in MLOps or DevOps engineering</li><li>
Proven leadership experience in managing AI or ML deployment projects</li><li>
Background in collaborating with data scientists and cloud engineers</li><li>
Expertise in building CI/CD pipelines in AWS or Azure platforms</li><li>
Skills in containerization using Docker and deploying applications in cloud environments</li><li>
Proficiency in infrastructure automation using Terraform</li><li>
Knowledge of managing data schemas in cloud data warehouses such as Azure and Snowflake</li><li>
Understanding of generative AI fundamentals and applications</li><li>
Capability to deploy and manage AI models and APIs in production</li></ul>
Nice to have<ul><li>
Familiarity with large language models (LLM)</li><li>
Experience with retrieval-augmented generation (RAG) systems</li></ul>
We offer<ul><li>
Opportunity to work on technical challenges that may impact across geographies</li><li>
Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications</li><li>
Opportunity to share your ideas on international platforms</li><li>
Sponsored Tech Talks &amp; Hackathons</li><li>
Unlimited access to LinkedIn learning solutions</li><li>
Possibility to relocate to any EPAM office for short and long-term projects</li><li>
Focused individual development</li><li>
Benefit package:<ul><li>
Health benefits</li><li>
Retirement benefits</li><li>
Paid time off</li><li>
Flexible benefits</li></ul></li><li>
Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)</li></ul></div>

Lead MLOps Gen AI Engineer

Xohani Solutions

Job role: Principal Data Engineer - Remote Job Type: Full Time Job Mode: REMOTE Experience: 8+ Years Work Hours: 1:00 PM &ndash; 10:00 PM IST Selection Process: OnlineJob Summary:We are looking for an accomplished Principal Data Engineer to lead the ideation, architecture, design and development of our next-generation enterprise data platform. This role requires a visionary technologist with deep hands-on expertise in cloud data engineering (GCP preferred), data architecture, and software engineering.You will work closely with cloud, security, and infrastructure architects to ensure seamless alignment with the organization's broader technology and business strategies.Job Role &amp; Responsibility:<ul><li>&middot; Lead the end-to-end architecture and development of a modern enterprise-scale data platform from the ground up.</li><li>&middot; Collaborate with cloud and security architects to ensure platform scalability, performance, and compliance.</li><li>&middot; Architect, design, and implement batch and real-time streaming data infrastructures and workloads.</li><li>&middot; Build and maintain data lakehouse architectures within the GCP ecosystem.</li><li>&middot; Design and develop connector frameworks and reusable data ingestion pipelines to source data from both on-premises and cloud systems.</li><li>&middot; Architect and implement metadata management, including data catalogs, lineage, quality, and observability frameworks.</li><li>&middot; Design and develop data quality frameworks and governance processes to ensure reliability and accuracy.</li><li>&middot; Develop microservices-based components using Kubernetes, Docker, and Cloud Run to abstract platform and infrastructure complexities.</li><li>&middot; Design and optimize data storage, transformation, and querying performance for large-scale datasets while ensuring cost efficiency.</li><li>&middot; Implement observability tooling (Grafana, Datadog) and DataOps best practices, including CI/CD and test automation.</li><li>&middot; Collaborate with data scientists and analysts to define data models, schemas, and advanced analytics capabilities.</li><li>&middot; Drive deployment, release management, and platform scalability initiatives.</li><li>&middot; Stay ahead of emerging data engineering trends, tools, and best practices to continuously evolve the platform.</li></ul>Skills:<ul><li>8+ years of proven experience in modern cloud data engineering and enterprise data platform architecture.</li><li>Demonstrated success in architecting and delivering large-scale greenfield data platform</li><li>projects.</li><li>Deep expertise in Google Cloud Platform (GCP) and its ecosystem &mdash; BigQuery, Cloud</li><li>Functions, Cloud Run, Dataform, Dataflow, Dataproc, SQL, Python, and Airflow.</li><li>Strong understanding of streaming technologies such as Kafka or Pub/Sub.</li><li>Hands-on experience with microservices architectures using Kubernetes, Docker, and Cloud Run.</li><li>Proven ability to design semantic layers and metadata-driven architectures.</li><li>Expertise in data modeling, data architecture, and data governance principles.</li><li>Experience with observability and monitoring tools (Grafana, Datadog).</li><li>Strong understanding of DataOps principles, including automation, CI/CD, and testing for data pipelines.</li><li>Experience architecting secure, scalable, and high-performance data solutions.</li></ul>Job Types: Full-time, Contractual / Temporary Contract length: 3 monthsPay: &#8377;1,900,000.00 - &#8377;4,000,000.00 per yearBenefits:<ul><li>Work from home</li></ul>Work Location: Remote

Principal Data Engineer

Fathom

<div>About the job
We are a pioneering AI company, marking our footprint on the global stage with a presence in Saudi Arabia, Poland, and Norway. As a pre-Series A startup, we are proudly backed by one of the world's leading corporations, underscoring our potential and the innovative spirit driving our mission. Our platform is engineered to address complex business challenges through cutting-edge AI solutions, with a particular emphasis on computer vision technologies. Our ambition is to launch a product that will revolutionize the industry by leveraging advanced computer vision capabilities.
We are seeking talented Senior Data Scientists to work with a client, one of the most recognized enterprise companies in the Oil &amp; Gas sector.
What you&rsquo;ll be doing<ul><li>
Lead the development and implementation of cutting-edge computer vision models and algorithms to solve complex problems, including but not limited to object detection, image recognition, and predictive maintenance for equipment.</li><li>
Collaborate closely with our product, marketing, and technical teams to integrate computer vision solutions that significantly enhance our AI/DataOps platform's value proposition to businesses.</li><li>
Drive data science projects from conception to delivery, focusing on computer vision applications, ensuring adherence to deadlines, data quality, and model effectiveness.</li><li>
Conduct in-depth research on the latest computer vision techniques and innovations to ensure our solutions remain at the forefront of AI technology.</li><li>
Translate complex computer vision findings into actionable insights, making them accessible to both technical and non-technical audiences.</li><li>
Optimize computer vision models for scalability and efficiency, ensuring they align with business goals and customer needs.</li></ul>
What We Offer:<ul><li>
Competitive salary and benefits package.</li><li>
A dynamic and challenging work environment.</li><li>
Opportunities for professional growth and development.</li></ul>
What you'll need<ul><li>
Proven experience as a Data Scientist with a strong focus on computer vision, demonstrated by a portfolio showcasing innovative computer vision projects in the tech industry, especially in AI/DataOps.</li><li>
Exceptional analytical and technical skills, with the ability to develop and implement advanced computer vision algorithms and models.</li><li>
Deep understanding of AI and DataOps concepts, trends, and technologies, with specialized expertise in computer vision.</li><li>
Experience working independently and delivering computer vision projects from scratch, demonstrating project management skills and the ability to meet tight deadlines.</li><li>
Adept at conducting comprehensive research to produce innovative and effective computer vision solutions.</li></ul>
Nice to have<ul><li>
Outstanding communication and interpersonal skills.</li><li>
Knowledge of applicable laws, codes, and regulations.</li></ul>
We're excited about the future and look forward to potentially having you on our team. Apply today to join our journey of growth and innovation!</div>

Senior Data Scientist

Search 8353+ Dataops engineer jobs near you this November. New roles added regularly across leading industries. Apply today.