Occupations

1982 roles mapped with the career paths between them and the skills they run on.

• Data AdministratorA Data Administrator manages databases and data systems to ensure data quality, security, and accessibility within an organization. They perform tasks like backing up data, monitoring database performance, managing user access permissions, and maintaining documentation of data structures and procedures. The role requires strong technical skills with database management systems and attention to detail, and typically suits individuals who are methodical, problem-solving oriented, and capable of managing complex technical environments.
• Data AnalysisProfessionals in data analysis roles extract insight from raw data using SQL and Python, building reports and dashboards in tools like Excel and Tableau or Power BI to help stakeholders make decisions. They apply statistical analysis to identify trends, anomalies, and correlations, working across departments such as marketing, operations, or finance depending on the organization. This role attracts analytically minded people who are comfortable moving between technical querying and clear business communication.
• Data Analysis and MathematicsData Analysis and Mathematics professionals extract insights from large datasets to support business or research decisions, writing SQL queries and Python scripts to clean and model data. They apply statistical analysis to uncover patterns and build data visualizations in tools like Tableau or Power BI, while still relying on Excel for quick analysis and reporting. Found across virtually every industry, they range from analysts to data scientists with backgrounds in statistics, math, or computer science.
• Data AnalystData analysts extract, clean, and interpret data to answer business questions, writing SQL queries and using Excel or Python to manipulate datasets before building dashboards in tools like Tableau or Power BI. They apply statistical analysis to spot trends and communicate findings to non-technical stakeholders across marketing, finance, or operations teams. The role is a common entry point into the data field and suits detail-oriented people who enjoy translating numbers into actionable insight.
• Data Analytics LeadA Data Analytics Lead oversees a team of analysts, establishing data strategy, managing analytical projects, and ensuring data quality and accessibility across an organization. The role combines technical expertise in analytics tools and databases with leadership responsibilities including mentoring analysts, communicating findings to stakeholders, and translating business questions into analytical work. The position suits detail-oriented professionals with strong technical foundations in data who also possess the communication skills and business acumen to guide teams and influence decision-making.
• Data Annotation SpecialistData Annotation Specialists label, rank, and correct text data in specific languages to train and improve machine learning models and AI systems. The work is detail-oriented and repetitive, involving careful analysis of language samples against guidelines, often using web-based annotation tools and platforms. The role suits people who are fluent in the target language, work well independently, and have patience for methodical, systematic tasks.
• Data ArchitectA Data Architect designs the structures and systems that organizations use to store, manage, and access data at scale, defining data models and standards that guide engineering teams. They design ETL and data pipeline processes, select and configure cloud data platforms like Snowflake, AWS, or Azure, and write SQL to validate and query architected systems. This senior technical role also encompasses data governance, ensuring data quality, security, and compliance across the organization.
• Data Center ManagerData Center Managers oversee the design, provisioning, and day-to-day operations of data center facilities and infrastructure, working to optimize systems for reliability, cost efficiency, and automation. The role involves managing hardware, cooling, power distribution, network connectivity, and staff while implementing monitoring and automation tools to ensure consistent uptime and performance of enterprise-scale systems. This position suits experienced infrastructure and operations professionals who enjoy strategic planning and technical leadership in complex, mission-critical environments.
• Data ConsultantData Consultants advise clients on how to leverage data and analytics to solve business problems and drive decision-making, combining technical data expertise with industry knowledge and business strategy. The role typically involves assessing a client's data infrastructure, identifying opportunities for improvement, and recommending solutions that align with their business objectives. Data Consultants often work across consulting firms or within organizations, collaborating with technical teams and business stakeholders to translate complex data concepts into actionable insights.
• Data EngineerA Data Engineer designs, builds, and maintains the pipelines and infrastructure that move and transform data for analytics and applications across an organization. Working closely with data scientists and analysts, they typically write Python and SQL, use Apache Spark for large-scale processing, and deploy ETL/data pipeline workflows on cloud platforms like AWS, Azure, or GCP. This role usually attracts detail-oriented software engineers with strong distributed-systems and data-modeling instincts.
• Data Governance AnalystA Data Governance Analyst supports an organization's data governance program by monitoring data quality, documenting metadata, and helping enforce data standards, usually within an IT or data management team. The role requires hands-on data governance and data quality management work, along with SQL skills to query and validate data and experience with data cataloging tools like Collibra or Informatica. This is often a mid-level role that serves as a stepping stone to becoming a Data Governance Manager or Director.
• Data Governance ManagerA Data Governance Manager builds and oversees the policies, standards, and processes that ensure an organization's data is accurate, secure, and properly used, typically sitting within IT, data, or compliance departments. The role centers on establishing data governance frameworks and data quality management practices, along with metadata management and regulatory compliance work around laws like GDPR and CCPA. Managers in this role commonly use data cataloging tools such as Collibra or Informatica and often have backgrounds in data management, compliance, or information systems.
• Data Governance SpecialistData Governance Specialists develop and implement frameworks and policies that manage how organizations collect, store, use, and protect data while maintaining quality and regulatory compliance. The role involves designing governance structures, establishing data standards, and working across technical and business teams to ensure consistent data management practices; tools and approaches may include data cataloging systems, metadata management, knowledge graphs, and compliance tracking. The position suits detail-oriented professionals who can bridge business and technical stakeholders and are comfortable with both strategic planning and operational execution of data policies.
• Data Management and EngineeringData management and engineering professionals design and maintain the pipelines and databases that move and store an organization's data, writing SQL and Python to build ETL pipelines and applying data modeling principles to structure information for analysis. They typically work with cloud data platforms like AWS or Snowflake to scale storage and processing for large datasets. This role sits at the foundation of any data-driven organization and appeals to detail-oriented engineers who enjoy building reliable, scalable infrastructure.
• Data ManagerA Data Manager oversees an organization's data infrastructure and the people who maintain it, writing and reviewing SQL to manage core databases while establishing data governance policies around quality, access, and compliance. They oversee data warehousing strategy and the ETL/data pipelines that feed it, and provide team leadership to data engineers and analysts reporting to them. This role typically sits within an IT or data/analytics department and is held by experienced data professionals who have moved from hands-on engineering or analysis into a managerial capacity.
• Data Migration LeadA Data Migration Lead oversees the planning, execution, and validation of large-scale data transfers between systems, databases, or platforms, ensuring data integrity and minimal downtime during transitions. The role involves technical coordination with IT teams, database administrators, and business stakeholders to design migration strategies, manage timelines and risk, and troubleshoot issues as they arise. This position typically requires strong technical knowledge of databases and data systems, project management skills, and the ability to communicate across technical and non-technical audiences during high-stakes operational changes.
• Data Mining AnalystA Data Mining Analyst sifts through large datasets to uncover patterns and trends that inform business decisions, writing SQL and Python code alongside dedicated data mining tools to extract and process information. They apply statistical analysis and machine learning techniques to build predictive models and validate findings. This analytical role suits someone with a strong quantitative background who enjoys working deep in the data to answer open-ended business questions.
• Data Quality AnalystA Data Quality Analyst is responsible for monitoring, profiling, and cleansing organizational data to ensure it is accurate, consistent, and fit for business use, typically sitting within a data governance, IT, or analytics team. Day-to-day work involves writing SQL queries to audit datasets, using data profiling and cleansing techniques alongside tools like Informatica, Talend, or Ataccama to detect anomalies, and performing root cause analysis to trace and fix recurring data issues at their source. This role suits a detail-oriented, methodical person who is comfortable moving between technical tools and Excel-based reporting to communicate findings to both technical teams and business stakeholders.
• Data ReporterA Data Reporter analyzes datasets and creates written reports, visualizations, or dashboards that communicate findings to stakeholders, often within journalism, business intelligence, or research contexts. The work typically involves querying databases, cleaning and validating data, and presenting insights in formats tailored to audience needs, often using tools like SQL, Excel, Tableau, or Python. The role suits detail-oriented individuals with strong analytical and communication skills who can translate complex data into clear, actionable narratives.
• Data Science ManagerA Data Science Manager leads a team of data scientists and machine learning engineers while maintaining hands-on technical involvement in building AI/ML products and solutions. The role blends people management—mentoring team members, managing performance, and overseeing project delivery—with active participation in algorithm design, model development, and technical architecture decisions. Data Science Managers typically work across cross-functional teams, collaborate with product and engineering stakeholders, and require both strong technical depth in Python, machine learning frameworks, and cloud platforms alongside demonstrated leadership experience.
• Data ScientistData scientists build statistical and machine learning models to solve business problems, writing Python and SQL to process data and applying statistical modeling techniques to uncover patterns others might miss. They partner with product and engineering teams to test hypotheses, run experiments, and present findings through data visualization, often bridging the gap between raw data and strategic decisions. The role typically requires strong quantitative training and appeals to people who enjoy both rigorous analysis and applied problem-solving.
• Data SpecialistA Data Specialist handles the practical, day-to-day work of keeping an organization's data accurate and usable, writing SQL queries and Excel formulas to pull and manipulate datasets on request. They spend significant time on data cleaning and data quality work to fix inconsistencies before analysis, build data visualization outputs like dashboards and charts for stakeholders, and perform routine database management tasks. This role is common across business operations, marketing, and analytics teams and is typically held by detail-oriented professionals early in a data or analytics career path.
• Data StewardA Data Steward is responsible for the day-to-day quality, accuracy, and proper use of specific data domains within an organization, acting as a bridge between business units and data governance teams. The role applies data governance frameworks and metadata management practices, using data cataloging tools such as Collibra, Informatica, or Alation alongside SQL to monitor and maintain data quality. Data Stewards typically have deep knowledge of the business data they oversee and work closely with data governance managers or analysts to enforce organizational standards.
• Data Testing ManagerA Data Testing Manager oversees quality assurance and testing processes for datasets, designing test scenarios, managing test data, and ensuring data quality standards are met throughout development workflows. The role combines technical data quality expertise with people management, requiring leadership of testing teams and collaboration with data engineers and analysts to embed quality practices across data pipelines. This position suits detail-oriented leaders with strong backgrounds in data QA who can balance technical rigor with team coordination.
• Data Warehouse DeveloperA Data Warehouse Developer designs and builds the structures that consolidate data from multiple source systems into a central repository for reporting and business intelligence. They write SQL and use ETL tools like Informatica or SSIS to load data, apply data modeling techniques such as star and snowflake schemas, and increasingly build these warehouses on cloud platforms like Snowflake or Redshift, often scripting supporting logic in Python. This position typically sits within IT or BI teams and suits methodical professionals who enjoy structuring data for consistent, efficient querying.

Find where you fit

Your work history places you on this map — each role you add connects you to an occupation, its career paths, and the open roles that match it.