This page tracks remote data engineer openings that are location-eligible for Illinois.
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Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable local laws, regulations, and ordinances.
Role Description We are looking for a talented Data Engineer II to join our growing and fast-paced Insider Risk Engineering team. In this role, you will work on developing and managing data pipelines, joining and filtering data sets, and building advanced insider risk detections to proactively identify and address potential threats. - Design, build, and optimize data pipelines to ingest, process, and prepare data for use in insider risk detection models. - Join, filter, and integrate diverse data sources to create comprehensive datasets that enable effective and accurate insider risk detections. - Work with large datasets, applying advanced data transformation techniques to ensure data quality and accessibility for risk detection. - Develop, test, and deploy insider risk detection models based on data-driven insights to proactively identify anomalous or risky behavior patterns. - Collaborate with insider risk team members to define and refine detection use cases, ensuring they are accurate, scalable, and aligned with business needs. - Share knowledge and actively contribute ideas in team technical discussions. - Maintain and monitor insider risk engineering systems to ensure reliable operation, security, and compliance with internal engineering standards and policies. - Join on-call rotations, lead incident response, and drive thorough root-cause analysis. - Document data processes, detection workflows, and system configurations to support future development and maintenance. - Use development and coding best practices (e.g., reusable, modular). - Own end-to-end quality for the code you deliver, including testing and DevOps automation. Qualifications - Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. - Preferred Qualifications: - Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent work experience. - 4+ years of experience in data engineering, data science, or a hybrid data engineering/data science role. - Proficiency in query languages (e.g., SQL, KQL). - Experience with object-oriented programming languages (e.g., Python, C#, Java, or C++). - Experience with security product usage such as Insider Risk Management or Sentinel. - Demonstrated ability to build and manage data systems in the cloud. - Experience with big data systems and tools, such as PySpark, Databricks, or Azure Synapse. - Familiar with data engineering best practices like layered data architecture, data modeling, and developing reliable and scalable data pipelines. - Strong understanding of engineering and security compliance standards, with experience in regulated environments. - Excellent problem-solving skills and attention to detail, with a proactive approach to identifying and mitigating risks. - Experienced working within agile frameworks such as Scrum and Kanban. Requirements - Candidates must be able to meet Microsoft, customer and/or government security screening requirements are required for this role. - Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. - Citizenship & Citizenship Verification: This role will require access to information that is controlled for export under export control regulations. - This position requires verification of citizenship due to citizenship-based legal restrictions. Benefits - Data Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year. - There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800 - $219,200 per year. - Certain roles may be eligible for benefits and other compensation. - Find additional benefits and pay information here .
Role Description Candidates MUST BE located in USA due to client's technical requirements. - Remote position - Must-Haves: Full fluency in English language. - Full Time Remote position - Hours: 9am to 3pm PST Mon-Fri - MUST BE AVAILABLE PACIFIC TIME ZONE - This position is expected to end towards the end of June, with potential extension as per client's needs Responsibilities - Data Evaluation & Annotation: Label and categorize text and images, ensuring accuracy and quality - Platform Management: Work within the client’s universal language platform to manage and evaluate language-based data - Trend Analysis: Track and assess data, identifying insights to enhance project quality - Quality Assurance: Ensure accuracy by proofreading and maintaining high-quality outputs - Process Improvement: Provide insights and recommendations to improve data relevance and performance - Adaptability & Collaboration: Work in a fast-paced environment with shifting priorities while maintaining communication with your team Qualifications - Fluency in English – Must have full professional proficiency in both written and spoken communication - Strong analytical skills – Ability to evaluate data logically and provide sound reasoning - Attention to detail – A sharp eye for spotting inconsistencies and ensuring high data accuracy - Time management skills – Ability to manage multiple tasks efficiently - Critical thinking & problem-solving – Ability to make data-driven decisions - Tech-savvy mindset – Comfortable navigating platforms and tools - Adaptability & teamwork – Willingness to collaborate and adjust to changing project needs Requirements - Work Authorization: Must have valid authorization to work in the U.S. - Background Check: Required for this role - Equipment: Must have a personal laptop or computer Benefits - 401(k) - Paid time off - Fully Remote Company Description Join Volga Partners, a dynamic U.S.-based company at the forefront of Artificial Intelligence (AI) and Machine Learning (ML), proudly partnering with leading technology giants and global multinational corporations. Why Join Us? - Fully remote role – Work from the comfort of your home - Entry to mid-level opportunity – Gain hands-on experience in data evaluation and AI - Flexible training hours – Get the support you need to succeed - This current opening is for full time. - Work with cutting-edge technology – Contribute to improving AI and language models
A fast-growing leader in online education, Coursera is an education-focused technology company headquartered in Mountain View, California. Founded in 2012, Coursera is backed by Si
Role Description We are looking for a Chief of Staff to join our team and serve as a strategic integrator for the Chief Data Officer, operating across a major function or business domain to connect strategy and execution. This role ensures that the Data organization scales effectively, translating company strategy into a cohesive operating system that drives alignment, accountability, and results across multiple teams. At Coursera, we’re evolving how we operate to enable sustained growth and agility. The Chief of Staff plays a central role in that evolution, designing and improving the frameworks that underpin performance, including planning, governance, decision-making, and resource allocation. Operating at the intersection of strategy and operations, this role enables the executive and leadership team to deliver Coursera’s goals with greater clarity, speed, and discipline. Objectives of this role: - Translate company strategy into functional operating systems that connect priorities, plans, and execution across teams. - Drive cross-functional alignment within and adjacent to the Data organization, ensuring shared accountability for results. - Design and evolve frameworks that bring structure, discipline, and visibility to planning, goal-setting, and performance tracking. - Enable high-quality decision-making through data, narratives, and governance models that clarify tradeoffs and resource allocation. - Ensure organizational readiness and adaptability, balancing scale with speed as Coursera continues to evolve. - Strengthen the leadership system within the Data org, increasing focus, follow-through, and clarity across teams. Responsibilities: - Manage and continuously improve the CDO Org operating rhythm, including timely review and action of key performance indicators (KPIs). - Partner with executive-enabling function - People, Finance, Administration - to drive CDO’s strategic change and improvement initiatives org-wide. - Drive the strategic and operational planning system for the CDO organization, defining and continuously improving processes that enable the CDO to effectively and efficiently manage their large team with ongoing visibility into results and impact. - Oversee a portfolio of strategic projects, structuring and driving to completion complex, ambiguous initiatives, steering large, cross-functional projects, and building consensus with senior leadership across the organization. - Lead employee engagement strategy, in collaboration with People Business Partner, crafting initiatives that foster a positive, inclusive, and dynamic work environment. Plan and execute internal communications within the team, ensuring that all team members are informed, aligned, and motivated. - Create cross-functional connections between the principal’s org and adjacent functions to accelerate decision-making and remove friction. - Facilitate strategic meetings, ensuring alignment and clarity on objectives, and drive follow-through on action items. Represent the CDO in certain cross-functional meetings and projects, advocating for their priorities and ensuring alignment with overall company strategy. - Build and develop relationships with the CDO’s direct reports and other individuals in critical roles - providing an unbiased ear - to understand the need and opportunities in existing ways of working and helping define new strategies to address. Qualifications - 12-15 years in a business or executive management role. - In-depth experience driving results in a Data organization. - Extremely versatile, dedicated to efficient productivity. - Experience defining, planning, and driving top-level strategic initiatives. - Excellent communicator in written and verbal form. - Demonstrated experience organizing and directing multiple teams and departments. - Proven track record of data-driven approach to complex decision-making. Preferred Qualifications - Master’s degree in Business Administration or similar field. - Experience with data analysis. - Experience with budget management. - Consulting experience with a focus on operations management. - Proven success in a project management role. - Nimble business mind with a focus on developing creative solutions. - Strong project reporting skills, with a focus on interdepartmental communication. Compensation This role is available in the following US Pay Zones: - US Zone 1: $188,480 - $235,600 - US Zone 2: $180,120 - $225,150 - US Zone 3: $167,200 - $209,000 - US Zone 4: $155,420 - $194,275 At Coursera, we offer competitive, zone-based pay aligned to your location, experience, and role level across four U.S. pay zones. Our total rewards package goes beyond salary, with comprehensive health and wellness benefits, bonus and RSU equity programs, and global perks designed to help you grow and thrive wherever you are.
Role Description We are looking for a Middle Data Engineer specialized in Azure Databricks to join our data platform team. The candidate will design and develop modern data pipelines and Lakehouse architectures, leveraging Azure Databricks, Spark, and Azure Data Factory, while integrating with existing SQL Server-based data warehouse environments, also evolving our data platform towards scalable, cloud-based data architectures, enabling advanced analytics and business intelligence. - Design, develop, and maintain data pipelines using Azure Databricks - Build and optimize data transformations using PySpark and SQL in Databricks - Implement and maintain Lakehouse architectures using Delta Lake - Develop ETL/ELT pipelines orchestrated through Azure Data Factory - Integrate data from multiple sources into the data platform and analytical layers - Design and maintain data models and data warehouse structures for analytics - Ensure data quality, scalability, and performance of large-scale data processing pipelines - Collaborate with BI teams to support Power BI and reporting platforms - Support and evolve existing SQL Server data platforms and ETL solutions (SSIS) when required - Contribute to the design of modern cloud-based data architectures Qualifications - 3+ years of experience in Data Engineering or Data Warehouse development - Experience with Azure Databricks - Experience developing data pipelines using PySpark and Spark SQL - Solid understanding of distributed data processing and big data concepts - Experience working with Delta Lake and Lakehouse architectures - Strong SQL skills and experience with SQL Server relational databases - Experience building data pipelines using Azure Data Factory - Experience handling large datasets and performance optimization Requirements - Nice to have: Experience with Spark optimization techniques (partitioning, caching, cluster tuning) - Experience with structured streaming in Databricks - Knowledge of CI/CD pipelines for data platforms (Azure Devops) - Familiarity with Power BI - Experience in migrating from traditional ETL process to cloud architectures Soft Skills - Strong analytical and problem-solving skills - Ability to work in collaborative environments and to adapt - Committed to continuous learning and professional development, with a keen focus on advancing cloud computing expertise - Team player - Good communication skills with technical and non-technical roles - Proactive, actively identifying improvements and proposing solutions - Comfortable working in dynamic environments where priorities and technologies evolve Benefits - Culture of Relentless Performance: join an unstoppable technology development team with a 99% project success rate and more than 30% year-over-year revenue growth - Competitive Pay and Benefits: enjoy a comprehensive compensation and benefits package, including health insurance, and a relocation program - Work From Anywhere Culture: make the most of the flexibility that comes with remote work - Growth Mindset: reap the benefits of a range of professional development opportunities, including certification programs, mentorship and talent investment programs, internal mobility and internship opportunities - Global Impact: collaborate on impactful projects for top global clients and shape the future of industries - Welcoming Multicultural Environment: be a part of a dynamic, global team and thrive in an inclusive and supportive work environment with open communication and regular team-building company social events - Social Sustainability Values: join our sustainable business practices focused on five pillars, including IT education, community empowerment, fair operating practices, environmental sustainability, and gender equality
Role Description A-TEK is seeking a Senior Data Engineer to support enterprise data modernization, cloud-native data engineering, analytics enablement, and data governance initiatives for Federal customers. This role focuses on designing and implementing scalable data platforms, automated ETL/ELT pipelines, and modern cloud-based data solutions supporting scientific, operational, and mission-critical environments. The ideal candidate combines strong hands-on engineering expertise with the ability to collaborate across technical and non-technical teams to modernize data ecosystems and improve enterprise data accessibility, quality, governance, and analytics capabilities. NOAA experience is preferred. This position is remote and requires the ability to obtain and retain a public-trust clearance. Responsibilities - Design, develop, and optimize enterprise data warehouses and large-scale ETL/ELT pipelines - Engineer cloud-native data processing solutions supporting structured, semi-structured, and unstructured data - Develop scalable ingestion and transformation frameworks for high-volume and real-time data processing - Support modernization of legacy data environments into cloud-based architectures - Design and implement data models, schemas, and database structures optimized for analytics and reporting - Develop metadata-driven automation, data quality validation, lineage tracking, and governance capabilities - Build and maintain reporting, analytics, and dashboarding solutions supporting operational and executive decision-making - Collaborate with architects, engineers, analysts, and business stakeholders to define technical requirements and implementation strategies - Support AI/ML and advanced analytics initiatives through scalable data engineering and MLOps-ready infrastructure - Implement Infrastructure-as-Code (IaC), CI/CD pipelines, and automated deployment processes - Perform database tuning, query optimization, and performance engineering activities - Support secure data management and compliance with Federal security and data governance requirements - Provide technical leadership, mentoring, and engineering best practices across project teams Qualifications - Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field - 7+ years of experience in data engineering, data warehousing, database engineering, or related disciplines - Strong experience designing and implementing ETL/ELT pipelines and enterprise data warehouse solutions - Experience with distributed processing frameworks and cloud-native data ecosystems - Strong experience with data modeling, database design, and dimensional modeling techniques - Experience implementing data governance, metadata management, data quality, and data integrity controls - Proficiency with SQL and Python-based data engineering and automation - Experience with cloud data platforms and services in AWS, Azure, or Google Cloud - Experience supporting large-scale, modern data modernization initiatives - Strong verbal and written communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders - Experience collaborating across cross-functional teams in Agile or DevSecOps environments Preferred Qualifications - NOAA or broader Federal civilian agency experience - Experience supporting scientific, environmental, geospatial, or research data environments - Experience with GIS or geospatial data platforms - Experience with AI/ML data engineering or MLOps support - Experience with Infrastructure-as-Code and CI/CD automation - Familiarity with metadata management, data catalogs, and enterprise governance frameworks - Experience with real-time streaming or event-driven data architectures - AWS or Azure certifications Preferred Technical Skills - SQL Server, PostgreSQL, Oracle, or cloud-native databases - Azure Data Factory, SSIS, Informatica, dbt, Airflow, or similar ETL frameworks - Azure Synapse, Databricks, Spark, Hadoop, Kafka, or distributed analytics platforms - Python, Pandas, NumPy, PySpark - Power BI, Tableau, SSRS, or enterprise analytics platforms - Docker, Kubernetes, Git, Azure DevOps, Jenkins, Terraform, or similar DevOps technologies - REST APIs and data integration services Compensation Salary Range: $160,000 – $170,000 annually (commensurate with experience, professional certifications and location) Benefits - Health, dental, and vision insurance - 401(k) with employer match - Paid time off - Professional development opportunities
Helping companies worldwide enable reliability through better lubrication and oil analysis processes.
• Define Data Platform Strategy: In partnership with senior leadership, define the vision, roadmap, and operating model for AssetWatch’s data platform, ensuring it supports analytics, product development, and AI initiatives across the organization. • Lead the Data Platforms Organization: Build, lead, and develop the data platforms team, establishing clear goals, accountability, and performance expectations. Develop managers and engineers while fostering a culture of ownership, collaboration, and continuous improvement. • Set Organizational OKRs: Partner with executive leadership to define strategic OKRs for the data platform organization and translate them into measurable goals for teams and individuals. • Own Data as a Company Asset: Establish the governance framework that ensures data across the organization is well-defined, trusted, and properly managed, including dataset ownership, data definitions, lineage, access controls, and lifecycle management. • Data Platform Architecture: Design and evolve AssetWatch’s cloud data platform using AWS technologies such as S3, Glue, Athena, Redshift, and Lambda to support scalable analytics, reporting, and AI workloads through MCPs. • Data Ingestion & Pipelines: Oversee the development and reliability of data pipelines ingesting information from product telemetry, APIs, and enterprise SaaS systems. • Curated Data & Data Modeling: Lead the creation of trusted datasets used for reporting, operational decision making, and machine learning. • AI-Ready Data Infrastructure: Ensure the company’s data platform is structured to support AI and machine learning initiatives by enabling reliable, well-modeled data inputs for ML pipelines and advanced analytics. • Enterprise Systems Data Integration: Partner closely with Enterprise Applications leadership to ensure systems such as Salesforce, finance platforms, and customer success tools integrate cleanly into the data platform. • Data Quality & Reliability: Establish monitoring and operational processes that ensure data accuracy, pipeline reliability, and data freshness. • Security, Privacy & Compliance: Work with IT and Security teams to ensure the data platform meets SOC2 and privacy requirements including access control, encryption, audit logging, and retention policies. • Operational Efficiency: Eliminate manual reporting workflows and redundant integrations by creating scalable, automated data pipelines and shared data models. • Cross-Functional Leadership: Lead highly visible initiatives that align teams across engineering, product, operations, and leadership to improve data reliability and organizational decision-making.
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Role Description We are looking for a Principal GenAI Data Engineer to join our IT Data Strategy team. This role is fully remote within the US, reporting to the Senior Manager, Enterprise AI Data Platform. We are seeking an experienced technical leader to drive the design and implementation of enterprise-grade Generative AI data ingestion, knowledge preparation, and platform architectures that enable scalable, production-ready GenAI applications. This role focuses on architecting robust pipelines and platforms for ingesting, processing, governing, and serving structured and unstructured enterprise data for AI/LLM workloads. The ideal candidate combines deep expertise in enterprise data architecture, unstructured data pipelines, GenAI platform engineering, and strong software engineering skills in Python. What you’ll do (Role Expectations) - Architect enterprise-scale GenAI data platforms for ingestion, transformation, enrichment, and serving of structured and unstructured data - Design scalable pipelines for enterprise knowledge ingestion from diverse data sources including documents, SaaS platforms, knowledge bases, collaboration tools, and databases - Define architecture for metadata extraction, chunking, enrichment, embeddings generation, and knowledge preparation workflows - Design AI-ready data models and storage strategies for vector, graph, and hybrid knowledge systems - Architect scalable unstructured data processing pipelines for text, images, PDFs, tables, and multimodal content Who You Are (Success Profile) - You act like an owner. Your passion for the mission fuels your bias for action. - You operate with integrity because you genuinely care about the outcome. - You adapt to what’s needed, navigating seamlessly between high-level strategy and hands-on execution. - You are a problem-solver. You seek out challenges because you are energized by finding solutions. - You lead with integrity. You do the right thing, even when it’s hard. - You think at scale. You connect your day-to-day work to the larger company mission and think globally. - You are a high-trust collaborator. You are ambitious for the team, not just yourself. What We’re Looking for (Minimum Qualifications) - Expert-level Python programming and software engineering capabilities - Experience building distributed/scalable data pipelines for AI workloads - Strong understanding of unstructured data extraction and processing pipelines - Experience with vector databases, graph databases, and metadata/knowledge storage systems - Hands-on experience with clustering, entity recognition algorithms, and modern retrieval strategies (including RAG, search, and agentic AI workflows) What Will Make You Stand Out (Preferred Qualifications) - Deep understanding of AI-ready data platform design principles and the ability to bridge platform/data engineering with GenAI/LLM application requirements - Experience with LLMOps / GenAIOps frameworks such as LangSmith, Evaluation Framework like Arize Phoenix, Weights & Biases, or MLflow - Familiarity with Agent Frameworks like LangGraph, CrewAI, or Google ADK Benefits - Various health plans - Time off plans for vacation and sick time - Parental leave options - Retirement options - Education reimbursement - In-office perks, and more!
Role Description We are seeking a detail-oriented and dependable Remote Data Entry Specialist to join our growing team. In this role, you will be responsible for accurately entering, updating, and maintaining information within company databases and systems. This is a fully remote position offering flexibility, paid training, and opportunities for professional growth. Salary: $25–$30 per hour Weekly pay available depending on employer policies. Responsibilities - Enter and update data accurately into company databases and spreadsheets - Review records for errors, inconsistencies, and missing information - Organize and maintain digital files and documentation - Verify data accuracy by cross-checking source materials - Communicate with internal teams to resolve discrepancies - Follow confidentiality and company data protection procedures - Meet daily and weekly productivity goals Qualifications - High school diploma or equivalent - Strong attention to detail and organizational skills - Basic computer knowledge and typing proficiency - Ability to work independently in a remote environment - Strong communication and time-management skills - Reliable internet connection and computer/laptop access Preferred Qualifications - Previous data entry, administrative, or customer support experience preferred but not required - Familiarity with Microsoft Excel, Google Sheets, and online databases is a plus Benefits - Fully remote position - Flexible scheduling options - Paid training provided - Career advancement opportunities - Supportive and collaborative work environment - Work-life balance with remote flexibility
Leading autonomous vehicle technology since 2007, Torc develops automated Level 4, Class 8 trucks with Daimler.
Role Description We are looking for a Software Engineer who is eager to learn and grow while helping build and support Linux- and cloud-based data systems. In this role, you’ll work closely with experienced engineers to contribute to AWS-based data ingestion, ETL, and storage solutions that enable analytics, simulation, and ML training across the company. - Create robust and resilient pipelines to process massive daily volumes of data created by vehicle fleets and simulation environments. - Build and support scalable pipelines as part of Torc’s Data Factory to deliver data for ML training at scale. - Scale Torc’s data lake through a distributed storage system, data crawling and discovery. - Promote and protect the integrity of data through validation, versioning, data provenance, and governance. - Support the expansion of Torc’s data lake through acquisition of additional data sets from internal and external sources. - Assist in the development and delivery of cloud-based solutions. - Collaborate with teams specializing in perception, planning, control, mapping and vehicle testing to develop solutions that support product delivery. - Support the implementation of emerging cloud-based capabilities that can extend our technology stack and improve our ability to build, deploy and test safety-critical software for self-driving vehicles. - Participate in the team’s on-call rotation to support our deployed systems during business hours. Here’s a list of some of the technologies we use to make all the above happen: - Managed services powered by AWS (Lambda, SFN, Batch, EventBridge, Athena, Glue) - Linux / Bash - Docker - Terraform - Python - React/Javascript - On-Call Tooling (Datadog, AWS Cloudwatch) - Databricks Qualifications - BS/MS Degree in Computer Engineering, Computer Science, or related field. - Experience writing code using Python. - Practical experience with Docker and containerization. - A strong commitment to test-driven development patterns, continuous integration and delivery, and infrastructure as code. - Experience with Linux and general bash scripting. - Experience deploying, troubleshooting, monitoring and maintaining Linux systems. Requirements - Strong organizational, time management, and communication skills working with a team orientation and collaborative style. - Experience developing cloud-based serverless solutions. - Experience with pandas, numpy and other Python-based data analysis libraries and tooling. - Knowledge of AWS serverless architectures (Lambda, Batch, ECS Fargate, Glue, Athena). - Experience with data storage and acquisition patterns for robotics and advanced driver assistance systems. - Knowledge of different database architectures, including but not limited to relational and NoSQL databases, vector stores, data warehousing and clustered, distributed data stores. - Experience with the Databricks platform, particularly for serving data, visualizations and jobs. - Experience with scaling data for ML and AI workloads using Ray. Benefits - A competitive compensation package that includes a bonus component and stock options. - 100% paid medical, dental, and vision premiums for full-time employees. - 401K plan with a 6% employer match. - Flexibility in schedule and generous paid vacation (available immediately after start date). - AD+D and Life Insurance.
• Design, build, and maintain scalable data pipelines using Python, Spark, and Airflow to support our core data acquisition and entity resolution engines. • Collaborate cross-functionally with AI/ML and Product teams to implement new features and AI-native products. • Proactively identify and resolve bottlenecks in our complex ETL processes, bringing a fresh perspective to refine and optimize our existing codebase. • Contribute to a robust engineering culture through rigorous code reviews, unit testing, and clear communication of design decisions. • Own the end-to-end delivery of roadmap tasks within two-week sprints, ensuring work meets high standards for quality, documentation, and performance. • Participate in roadmap planning and story refinement, eventually taking ownership of major epics that drive our long-term product defensibility.
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Python, ETL, Data Engineering, Databricks, SQL, PySpark
