data warehouse engineer

Cwill

<div>CWILL (pronounced &quot;quill&quot;) is the post-purchase and retention suite built for Shopify.
With strong product-market fit and expanding US operations, we're building out our security and compliance capabilities to meet global data privacy standards.
Learn more: www.cwill.com
I. Basic Information 
Work Authorization
Green Card / U.S. Citizen required (we do nor sponsor)
Job Title
Data Engineer
Focus Areas
Data ingestion, data lakehouse, data warehouse, data platform, data service APIs, data quality &amp; engineering agent development
Level
Junior to mid-level with high growth potential
Location
United States &mdash; on-site, remote, or hybrid (per company requirements)
Employment Type
Full-time
Collaborating Teams
CWILL Data Engineering, Data Analytics, Business, Product, and Technology teams
Language
English required; Mandarin is a strong plus
Cross-Timezone Work
Must maintain a regular collaboration window with the China team; strong async communication and documentation skills required (approx. 2 hrs/day overlap needed)
Collaboration Frequency
Every 1&ndash;2 days; approx. 2 hrs per session. Candidates in western US time zones preferred for scheduling. 
II. Role Positioning 
CWILL is building data infrastructure to support business operations, product capabilities, customer service, analytics, and intelligent applications. As a US-side data engineer, you will participate in multi-source data ingestion, data lakehouse and warehouse development, data quality governance, data platform capability building, and AI Agent engineering automation exploration. 
We are looking for candidates with a solid foundation in SQL, Python, and data engineering &mdash; someone who can, with guidance from the existing data team, progressively take ownership of data ingestion, modeling, quality, and service tasks, while collaborating effectively with domestic data engineering, analytics, and business teams. 
This is not a pure data analysis, BI reporting, or one-off scripting role. It is a comprehensive data engineering position focused on data integration, data warehouse development, data platform capabilities, data services, and engineering automation. 
III. Role Mission 
Through stable, well-structured, and scalable data engineering capabilities, help the company unify, govern, model, and serve data scattered across business systems, SaaS platforms, external channels, and internal systems &mdash; improving the usability, accuracy, timeliness, and reusability of CWILL&rsquo;s data assets. 
This role is expected to continuously drive:<ul><li> 
More standardized data source ingestion</li><li>Clearer data lakehouse and warehouse structure</li><li>More automated data quality monitoring</li><li>More platform-driven data service capabilities</li><li>Progressive adoption of agent-based and automated approaches for data development, troubleshooting, documentation, and quality checks</li></ul> 
IV. Key Responsibilities 
1. Data Ingestion &amp; Pipeline Development<ul><li>Ingest data from internal and external business systems, third-party platforms, SaaS products, and external data sources; handle data collection, sync, cleansing, and loading</li><li>Participate in building offline and real-time data pipelines using SeaTunnel, Kafka, Flink, Spark, or similar technologies to improve ingestion stability and processing efficiency</li><li>Handle practical challenges in data sync: authentication, pagination, rate limiting, failure retry, incremental sync, backfill, schema changes, and task anomalies</li></ul> 
2. Data Warehouse &amp; Data Modeling<ul><li>Participate in layered data warehouse development across ODS, DWD, DWS, and ADS layers; build and maintain data models</li><li>Support business domain modeling, metric standardization, shared data model development, and core table maintenance</li><li>Optimize data organization and query performance on OLAP engines such as Doris to provide stable data support for product, operations, growth, customer success, and management analytics</li></ul> 
3. Data Quality &amp; Data Governance<ul><li>Build and maintain data quality rules for core data pipelines; ensure data accuracy, completeness, consistency, and timeliness</li><li>Participate in data validation, anomaly detection, alerting, and issue resolution; help improve stability of critical data pipelines</li><li>Contribute to data governance capabilities including DataHub or similar tools; improve metadata management, data lineage, data asset catalog, and data standards</li></ul> 
4. Data Platform &amp; Data Services<ul><li>Participate in building data platform capabilities including data development, task scheduling, monitoring, quality management, governance, and service delivery modules</li><li>Use tools such as DolphinScheduler and StreamPark for task management, scheduling orchestration, and real-time task operations</li><li>Support the data service layer by delivering standardized APIs, metric services, and data capabilities to internal systems, analytics applications, and business tools</li><li>Support underlying data for tools like Superset; ensure data availability for BI dashboards, metric boards, and business monitoring</li></ul> 
5. AI Agent &amp; Engineering Automation<ul><li>Participate in designing and implementing data development automation tools and engineering agents</li><li>Explore AI agent applications in data development, governance, quality detection, task operations, anomaly diagnosis, and documentation generation</li><li>Leverage large language models and automation tools to improve data engineering efficiency, task stability, and platform intelligence</li></ul> 
Requirements 
Must-Have 
Experience<ul><li>1&ndash;4 years of experience in data engineering, data platforms, data warehousing, backend development, analytics engineering, or a related role</li><li>Real project experience in data ingestion, data pipelines, data warehouse development, data modeling, data services, or data platform work</li><li>Strong learning ability and execution skills; able to independently drive small-to-medium data engineering tasks with clear objectives</li></ul> 
SQL Skills<ul><li>Proficient in SQL for querying, cleansing, aggregation, deduplication, comparison, validation, and metric calculation</li><li>Familiar with joins, window functions, CTEs, aggregation analysis, incremental logic, and basic performance optimization</li><li>Understands data warehouse layering concepts: fact tables, dimension tables, subject domains, metric definitions, and shared models</li></ul> 
Data Development<ul><li>Proficient in Java or Python for API integration, data processing, automation scripting, and file handling</li><li>Understands common engineering patterns: REST APIs, OAuth/API keys, pagination, rate limiting, retry logic, error handling, logging, and task idempotency</li><li>Good code structure habits; writes clean, maintainable, and reusable code</li><li>Familiar with Git, code review practices, README documentation, logging, testing, and collaborative engineering workflows</li></ul> 
Pipeline &amp; Platform Tools<ul><li>Familiar with one or more of: SeaTunnel, Kafka, Flink, Spark (data integration, real-time, or offline processing)</li><li>Familiar with one or more of: Doris, ClickHouse, Snowflake, BigQuery, Redshift, Databricks, PostgreSQL (data warehouse, OLAP, or lakehouse systems)</li><li>Familiar with one or more of: DolphinScheduler, StreamPark, Airflow, Dagster, Prefect, dbt (scheduling, development, or task management tools)</li><li>Understands data pipeline operations: scheduling, dependencies, monitoring, failure retry, backfill, version management, and deployment processes</li><li>Candidates are not expected to master all tools, but must have a solid data engineering foundation and the ability to quickly learn new tech stacks</li></ul> 
Data Quality &amp; Governance Mindset<ul><li>Understands data quality dimensions: accuracy, completeness, consistency, uniqueness, timeliness, and anomaly detection</li><li>Proactively designs data validation rules and can identify and locate data anomalies</li><li>Familiar with metadata management, data lineage, data asset catalogs, and data standards; experience with DataHub or similar platforms is a plus</li></ul> 
Collaboration &amp; Communication<ul><li>Able to communicate data requirements with analysts, business stakeholders, backend engineers, and product managers</li><li>Clearly describes problems, solutions, risks, progress, and deliverables</li><li>Comfortable with cross-timezone collaboration; strong written and spoken English communication skills</li><li>Willing to participate in regular fixed collaboration sessions with China-based teams and drive work through documentation and async communication</li></ul> 
Nice-to-Have<ul><li> 
Experience integrating third-party SaaS data: CRM, ERP, marketing platforms, customer service systems, logistics, e-commerce, payment systems, or ad platforms</li><li>Experience building data lakehouses, data middle platforms, data platforms, or enterprise-level data warehouses</li><li>Experience developing data service APIs, metric services, internal data products, or lightweight backend services</li><li>Experience with data quality frameworks, data lineage, metadata management, data catalogs, observability, or monitoring and alerting</li><li>AWS, GCP, or Azure cloud platform experience</li><li>Docker, CI/CD, Terraform, Kubernetes, or basic DevOps experience</li><li>Experience with LLMs, AI Agents, code generation, automated testing, task inspection, data quality agents, or engineering efficiency tooling</li><li>Experience with cross-border teams, international business, supply chain, e-commerce, logistics, marketing, or customer success data scenarios</li></ul> 
Benefits 
Starting Pay: 90 - 130k depends on experiences, open to negotiation
401(k)
PTO
Paid Holidays
Insurance</div>

Data Engineer - Bilingual Mandarin required

sonnen Egypt

<div>
 
 Standort
 
 
 
 Cairo, EG
 
 
 
 Stellen-ID
 
 : 4758
 
 
 Join the energy revolution with #teamsonnen!
 
 
 At sonnen, we&rsquo;re driven by a clear goal: creating a future powered by clean, affordable energy for everyone. That&rsquo;s why we make our customers independent &ndash; not only from fossil fuels, but also from rising electricity costs.
 
 
 The key to this independence is our intelligent, all-in-one energy system. It combines solar panels, battery storage, energy tariffs, and wallboxes &ndash; all developed and manufactured in Germany.
 
 
 As the first and only provider in Germany, we also connect thousands of home batteries into one shared network: the sonnenVPP, our industry-leading virtual power plant.
 
 
 In short: every day, we&rsquo;re working to shape the energy future. And we&rsquo;d be thrilled to have you join us!
 
 
 We are seeking a Data Engineer (m/f/d) to join our team and play a pivotal role in enabling our Business Intelligence and Data Science teams. As a Data Engineer, you will be responsible for maintaining and enhancing our AWS-based analytics platform, provisioning data from various sources, and enabling the development and stable operation of analytical solutions. We&rsquo;re looking for someone who shares our values, who isn&rsquo;t afraid to challenge existing processes, and who would like to work on innovative solutions in a fast-moving environment. If this sounds like you, then don&rsquo;t hesitate to get in touch.
 
 
 
 What you will do to help drive the energy transition:
 
 
 
 <ul>
 <li>
 (Senior) Define and design the architecture of our analytics platform, ensuring scalability, performance, and reliability.
 </li>
 <li>
 You design and build scalable data pipelines, ETL processes, and data lake and data warehousing solutions to support our analytics solutions.
 </li>
 <li>
 You develop and maintain data integration processes with a variety of structured and unstructured data sources.
 </li>
 <li>
 You implement, test, and maintain infrastructural components of sonnen&rsquo;s analytics platform and deploy and maintain data models.
 </li>
 <li>
 You implement data quality checks and monitoring mechanisms to ensure accuracy, completeness, and consistency of data.
 </li>
 <li>
 You define coding principles and support data scientists and analysts in implementing algorithms into operational solutions.
 </li>
 <li>
 Adhere to stringent quality assurance and documentation standards, utilizing version control and code repositories such as Gitlab.
 </li>
 <li>
 You stay up to date with emerging trends and technologies in data engineering and assess their potential applications to our business needs.
 </li>
 <li>
 (Senior) Share your knowledge by coaching/pair coding with more junior engineers.
 
 
 </li>
 </ul>
 
 What You Will Need On That Journey
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science or a related technical field.
 </li>
 <li>
 +3 years of relevant employment experience in roles such as Data Scientist, Data Engineer, or Data Architect.
 </li>
 <li>
 +3 years of experience with ETL tools, Data Modeling, and Data Architecture.
 </li>
 <li>
 Experience with Big Data technologies such as Hadoop, Hive, and Spark.
 </li>
 <li>
 Ability to translate organizational goals into technical solutions.
 </li>
 <li>
 Experience with Infrastructure as Code (experience in Terraform and Ansible are a plus).
 </li>
 <li>
 Proficiency in Python, SQL, and NoSQL.
 </li>
 <li>
 Excellent communication and project management skills.
 
 
 </li>
 </ul>
 
 Stellensegment:
 
 Data Warehouse, Computer Science, Business Intelligence, Project Manager, Quality Assurance, Technology
</div>

Data Engineer (m/f/d)

Valleysoft | Center of Excellence

<div>
 Valleysoft, a reputable IT services company, is seeking a skilled Data Engineer to join our dynamic team. The successful candidate will be responsible for designing, developing, and maintaining scalable data solutions to support business analytics and decision-making processes.
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design, build, and optimize data pipelines and ETL processes for collecting, transforming, and storing data across multiple sources
 </li>
 <li>
 Develop and maintain data warehouses, data marts, and data lakes to enable efficient data access and analysis
 </li>
 <li>
 Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver relevant solutions
 </li>
 <li>
 Ensure data quality, consistency, and security throughout the data lifecycle
 </li>
 <li>
 Monitor and troubleshoot data pipeline performance and implement improvements
 </li>
 <li>
 Keep up-to-date with emerging data engineering technologies and best practices
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Build and maintain data warehouse and data marts, including ODS and internal departmental marts
 </li>
 <li>
 Gather, process, maintain, and analyze large datasets, ensuring data accuracy and quality
 </li>
 <li>
 Design, automate, and support ETL pipelines and data flows across multiple applications
 </li>
 <li>
 Create logical and physical data flow models and mapping designs for ETL processes
 </li>
 <li>
 Strong SQL skills (performance tuning, index management) and solid understanding of database structures
 </li>
 <li>
 Strong understanding of data modeling concepts
 </li>
 <li>
 Familiarity with SQL and NoSQL storage, and Big Data technologies (Hive, Impala, YARN, Kafka, etc.)
 
 
 </li>
 </ul>
 Informatica-specific requirements:
 
 
 <ul>
 <li>
 Hands-on experience with Informatica PowerCenter development (mappings, sessions, workflows)
 </li>
 <li>
 Strong knowledge of Informatica transformations (e.g., Lookup, Joiner, Aggregator, Expression, Router, Sorter) and performance tuning
 </li>
 <li>
 Experience with Informatica Developer
 </li>
 <li>
 Experience with Informatica B2B is a plus
 </li>
 <li>
 Ability to design, automate, monitor, and troubleshoot ETL jobs, including scheduling
 
 
 </li>
 </ul>
 Banking sector requirements (preferred):
 
 
 <ul>
 <li>
 Previous experience in the banking sector, preferably business banking, including working with banking datasets
 </li>
 <li>
 Strong understanding of data quality and reconciliation expectations in banking environments
 </li>
 <li>
 Experience working under regulated environments and change control practices is a strong plus
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Private Health Insurance
 </li>
 <li>
 Training &amp; Development
 </li>
 </ul>
</div>

Data Engineer (+3 Years Experience)

Shields Group Search

<div>
 
 
 Data Engineer
 
 
 
 
 Hybrid in NYC
 
 
 
 
 Full-Time
 
 
 
 
 $175,000-$225,000 base + upside depending on experience
 
 
 
 
 
 
 
 About the Company
 
 
 
 Shields Group Search is partnering with an innovative private banking and wealth infrastructure company building modern tools for modern clients. Their platform is designed to help private investors access liquidity more easily while driving transparency into historically opaque markets, including fine art and commercial real estate.
 
 
 
 
 
 They are hiring a
 
 Data Engineer
 
 to help build a world-class data infrastructure that supports the modernization of private banking for independent wealth managers and family offices. This person will be responsible for designing, building, and maintaining robust data pipelines, ETL processes, and data warehousing solutions that enable analytics and drive insights across the platform.
 
 
 
 
 
 You will work closely with engineering and product teams to architect scalable, reliable data systems. The stack includes
 
 Python, SQL, cloud data warehousing platforms, and modern data engineering tooling
 
 .
 
 
 
 
 
 
 About the Role
 
 
 
 This position reports directly to the
 
 Head of Engineering
 
 . The ideal candidate will have meaningful educational and/or professional experience designing and implementing scalable data systems, building ETL pipelines, and writing clean, maintainable, well-tested code.
 
 
 
 
 
 This team is looking for someone who is genuinely excited to spend most of their day coding and building scalable systems, while also contributing architectural input. They would strongly prefer someone in
 
 NYC
 
 , and
 
 2-3 days per week in-office
 
 should be expected. They also want someone who is comfortable building with and using
 
 agentic systems
 
 . This is not the right fit for someone optimizing primarily for work/life balance.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Participate in the full software development life cycle from planning to deployment
 </li>
 <li>
 Design and build scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources
 </li>
 <li>
 Collaborate with the team to design, develop, unit test, and support new features
 </li>
 <li>
 Strive for high quality and rapid output through agile software development best practices
 </li>
 <li>
 Architect data warehouses and data lakes, optimizing for query performance and cost efficiency
 </li>
 <li>
 Perform code reviews and provide constructive feedback to peers
 </li>
 <li>
 Maintain and improve the tech stack
 </li>
 <li>
 Develop flexible and well-structured data pipelines and data warehouse schemas
 </li>
 <li>
 Implement effective security protocols, data protection measures, and storage solutions
 </li>
 <li>
 Troubleshoot, debug, and upgrade software
 </li>
 <li>
 Ensure software meets all requirements of quality, security, and configurability
 </li>
 <li>
 Contribute to documentation, tests, and automation pipelines
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Software Engineering, or a related field
 </li>
 <li>
 Minimum of 3 years of experience in data engineering, ETL development, or analytics engineering, ideally within fintech or financial services
 </li>
 <li>
 Advanced proficiency in Python and SQL for data pipeline development and analysis
 </li>
 <li>
 Familiarity with CI/CD tools
 </li>
 <li>
 Experience with data warehousing platforms such as Snowflake, BigQuery, Redshift, or similar, as well as modern ETL tools
 </li>
 <li>
 Strong knowledge of the software development lifecycle
 </li>
 <li>
 Experience with testing and debugging
 </li>
 <li>
 Proficient understanding of code versioning tools such as Git
 </li>
 <li>
 Excellent problem-solving skills and attention to detail
 </li>
 <li>
 Excellent communication and teamwork skills
 </li>
 <li>
 Ability to work independently and take initiative
 </li>
 <li>
 Willingness and ability to build with agentic systems in a practical, hands-on way
 </li>
 </ul>
 
 
 
 
 
 Why This Role
 
 
 
 This is an opportunity to help architect a state-of-the-art platform and partner with an experienced leadership team during a period of rapid development. The team has additional flexibility on compensation for stronger candidates, with total base salary landing closer to
 
 $200,000-$225,000
 
 for candidates with more experience.
 
</div>

Data Engineer

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><div>Job Title: Data Engineer

Job Summary: 
We are looking for a skilled Data Engineer to design, develop, and optimize scalable data pipelines and transformations. The ideal candidate will have hands-on experience with DBT, Snowflake, and workflow orchestration tools, along with strong SQL and data modeling expertise.

Key Responsibilities:
<ul>
<li>Develop and maintain data models and transformations using DBT and Snowflake</li>
<li>Optimize Snowflake performance and improve query efficiency</li>
<li>Schedule, manage, and monitor data workflows using Control-M</li>
<li>Build and maintain scalable, reliable data pipelines</li>
<li>Collaborate with cross-functional teams to support data-driven initiatives</li>
</ul>
Required Skills:
<ul>
<li>Strong proficiency in SQL and data modeling</li>
<li>Hands-on experience with Snowflake and DBT</li>
<li>Experience with Control-M or similar scheduling/orchestration tools</li>
<li>Solid understanding of data warehousing concepts and performance tuning</li>
</ul></div></div></div></div><div><div><div>Location</div>
<div>San Antonio, TX</div>
</div><div><div>Job Function</div>
<div>TECHNOLOGY</div>
</div><div><div>Role</div>
<div>Engineer</div>
</div><div><div>Job Id</div>
<div>416516</div>
</div><div><div>Desired Skills</div>
<div>Control M</div>
</div><div><div>Salary Range</div>
<div>$85,000-$100,000 a year</div></div></div></div><div></div>

Self Financial, Inc.

<div>
 Self Financial is a venture-backed, high-growth FinTech company with a mission to increase economic inclusion and financial resilience by empowering people to build credit and build savings.
 
 
 We're looking for people who share our passion and are driven to tackle challenges, find solutions and make the financial space better for the communities we serve.
 
 
 Our team is passionate about challenging the status quo of the credit industry by providing people accessible tools to take control of their credit. Executing on our mission requires deep collaboration across our teams to ensure our products reach the people who can benefit from them the most, particularly the 100 million+ Americans who have no or low credit.
 
 
 We celebrate diversity and are committed to creating an inclusive environment for all employees. To that end, we seek to recruit, develop and retain the most talented people from a diverse candidate pool.
 
 
 
 About the Role:
 
 
 
 As our Staff Data Engineer, you will be responsible for organizing plans that drive outcomes and making a direct impact on our mission. We want you to provide technical leadership to your teammates through coaching and mentorship, and collaborate cross-functionally to implement impactful improvements to our product.
 
 
 As part of the Self Financial Data Engineering Team, your role will be to ensure that data remains a strategic asset for Self Financial by delivering timely, high-quality, and purpose-built data to our team members. Our team supports Self Financial's internal Analytics, Machine Learning, and Business Intelligence organizations.
 
 
 
 What you will do:
 
 
 
 <ul>
 <li>
 Operates as part of a cross functional product development team that includes Architecture, Infrastructure, and Product Management
 </li>
 <li>
 Your primary focus will be on leading the data pipeline, modeling, and populating data schemas within Self Financial's Data Environment for use in business intelligence and data analysis activities.
 </li>
 <li>
 Your day-to-day activities will include:
 </li>
 <ul>
 <li>
 Collaborating closely with Product Management to translate Self Financial's strategic vision into actionable projects.
 </li>
 <li>
 Architecture design, project analysis, work break down and planning.
 </li>
 <li>
 Creating Physical and Logical Data Models with large, complex data sets
 </li>
 <li>
 Managing data pipeline, ETL/ELT processes using SQL and Python
 </li>
 <li>
 Maintaining data lifecycle and quality standards
 
 </li>
 </ul>
 </ul>
 
 Who you are:
 
 
 
 <ul>
 <li>
 8+ years of experience with database development, database integration, and data analytics tools
 </li>
 <li>
 8+ years of experience designing and implementing complex Data Warehouse and Data Lake data models (Kimball)
 </li>
 <li>
 Willingness to embrace the responsibilities of team leadership and accountability for team results
 </li>
 <li>
 Proficient in managing Data ETL/ELT with large data sets
 </li>
 <li>
 Experience with columnar data structures such as Amazon RedShift
 </li>
 <li>
 Familiarity with AWS data warehousing tools
 </li>
 <li>
 Experience with common software engineering tools such as Git, JIRA, Confluence and similar platforms
 </li>
 <li>
 Familiarity with Apache Airflow and Python
 </li>
 <li>
 Excellent listening, interpersonal, written, and oral communication skills
 
 
 </li>
 </ul>
 
 
 Base salary range: $160,000-195,000 annually. Individual pay and level is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.
 
 
 
 
 
 Benefits and Perks:
 
 
 
 We have the compensation and benefits you expect. But there's one thing that Self Financial can offer that many companies cannot: we can positively change the world, while making a profit. We are a team of Builders, empowering our customers to build their dreams. We have a Do the Right Thing ethos in all that we do, and we hope you value that approach, too.
 
 
 
 Our perks include:
 
 
 
 <ul>
 <li>
 Company equity in the form of Stock Options
 </li>
 <li>
 Performance-based bonuses
 </li>
 <li>
 Generous employer-paid health, vision and dental insurance coverage
 </li>
 <li>
 Flexible vacation policy
 </li>
 <li>
 Educational assistance
 </li>
 <li>
 Free gym membership
 </li>
 <li>
 Casual dress code
 </li>
 <li>
 Team building events and activities
 </li>
 <li>
 Remote work arrangements/ flexible work schedule
 </li>
 <li>
 Paid parental leave
 
 
 </li>
 </ul>
 Self Financial requires all employees hired to successfully pass a background check.
 
 
 We are an Equal Opportunity Employer.
 
 
 
 
 At this time, we are only able to consider applicants who are U.S. Citizens or Green Card Holders for employment opportunities. We appreciate your understanding.
 
 
</div>

Staff Data Engineer

Data Engineer, Product Analytics (University Grad)

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Data Engineer - Bilingual Mandarin required

Data Engineer (m/f/d)

Data Engineer (+3 Years Experience)

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Staff Data Engineer

Data Engineer, Product Analytics (University Grad)