Role Description Zur Unterstützung strukturierter digitaler Abläufe suchen wir zuverlässige Personen für organisatorische Tätigkeiten im Homeoffice. Die Aufgaben erfolgen vollständig online und umfassen unter anderem: - Strukturierte Pflege und Aktualisierung digitaler Datensätze - Koordination und Verwaltung von Terminübersichten nach Vorgaben - Unterstützung organisatorischer Abläufe im digitalen Arbeitsalltag - Bearbeitung standardisierter Verwaltungsprozesse über Online-Tools - Dokumentation erledigter Aufgaben zur internen Übersicht Die Tätigkeit wird auf selbstständiger Basis durchgeführt und eignet sich besonders für Personen, die flexibel, strukturiert und ortsunabhängig arbeiten möchten. Qualifications - Sorgfältige und strukturierte Arbeitsweise - Zuverlässigkeit und eigenverantwortliches Arbeiten - Grundkenntnisse im Umgang mit digitalen Anwendungen und Online-Tools - Gute organisatorische Fähigkeiten und ein sicherer Umgang mit Informationen - Freundliche und professionelle Kommunikation im digitalen Austausch - Sehr gute Deutschkenntnisse in Wort und Schrift Hinweis: Vorkenntnisse sind nicht zwingend erforderlich, da eine strukturierte Einarbeitung in die Abläufe erfolgt. Benefits - Flexible Zeiteinteilung im Rahmen der Aufgaben - Ortsunabhängige Tätigkeit im Homeoffice - Strukturierte Einarbeitung mit klaren Abläufen - Digitale Zusammenarbeit in einem modernen Arbeitsumfeld - Langfristig angelegte Zusammenarbeit auf selbstständiger Basis - Unterstützung durch feste Ansprechpartner während der Einarbeitung Company Description Klarwerk Digital unterstützt strukturierte digitale Abläufe im Bereich Organisation, Datenpflege und administrativer Online-Prozesse. Der Fokus liegt auf klaren Arbeitsabläufen, moderner Remote-Zusammenarbeit und einer flexiblen digitalen Unterstützung organisatorischer Tätigkeiten.

Title: Technical Lead Data Engineering Location: Charlotte/ United States - Job category: Technology & Engineering - Work model: Work from Home Job Description: About the role We are seeking a highly experienced Technical Lead - Data Engineering with 10+ years of expertise delivering enterprise-scale data solutions on AWS. This role is suited for a seasoned, hands-on developer who combines deep technical proficiency with strategic thinking to design, build, and modernize data platforms. You will develop and implement complex data engineering solutions and contribute to large-scale cloud transformation initiatives, delivering high-quality, scalable, and performant data systems that power advanced analytics and business insights. In this role, you will: - Design, build, and optimize scalable data engineering solutions using AWS cloud services. - Develop and maintain robust ETL pipelines using AWS Glue (PySpark/Python) to process large-scale data efficiently. - Implement and enhance data integration frameworks leveraging Glue Data Catalog, Crawlers, and S3/JDBC sources. - Develop high-performance data processing logic using PySpark, Python, and SQL. - Contribute to cloud data migration initiatives from on-premises systems to AWS (RDS PostgreSQL/Aurora) using AWS SCT, DMS, or custom frameworks. - Orchestrate and manage data workflows using AWS Step Functions, Glue Workflows, and event-driven services. - Collaborate with cross-functional teams to understand data requirements and deliver scalable data solutions. - Monitor, troubleshoot, and optimize data pipelines using CloudWatch and other AWS monitoring tools. - Ensure data quality, performance, and reliability across all data engineering processes. - Follow best practices in coding, testing, and deployment to maintain high-quality deliverables. Work model: We strive to provide flexibility wherever possible. Based on this role's business requirements, this is a remote position open to qualified applicants in Charlotte, NC. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs. The working arrangements for this role are accurate as of the date of posting. These may change based on the project you are engaged in, as well as evolving business and client requirements. We will always be transparent about role expectations. Please note: Some roles may require in‑person interviews at Cognizant offices or client locations based on project needs. What you need to have to be considered - 10+ years of experience in IT with a strong focus on Data Engineering and Analytics. - Proven hands-on experience designing and developing scalable data pipelines using Apache Spark (PySpark). - Strong expertise in AWS services, including Glue, S3, Lambda, Step Functions, Athena, RDS (PostgreSQL/Aurora), EventBridge, SNS, SQS, SES, and CloudWatch. - Extensive experience building and optimizing ETL pipelines using AWS Glue (PySpark/Python). - Experience in data migration from on-premises systems to AWS using tools such as AWS SCT and DMS or custom frameworks. - Strong programming skills in Python, SQL, and UNIX Shell scripting. - Experience working with Glue Data Catalog, Glue Crawlers, and handling structured and unstructured data sources. - Solid understanding of data modeling, performance tuning, and optimization techniques for large-scale datasets. - Hands-on experience with UNIX/Linux environments. - Ability to work independently in a fast-paced environment and contribute to complex technical solutions. - Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience). This will help you stand out - Experience with serverless and event-driven architectures on AWS. - Strong understanding of data lake and data warehousing concepts. - Hands-on experience with performance tuning and cost optimization in AWS data pipelines. - Familiarity with reporting and BI tools such as Cognos. - Experience working with large-scale, high-volume data processing systems. - Exposure to CI/CD pipelines and DevOps practices for data engineering workflows. - Strong problem-solving skills with the ability to troubleshoot complex data and system issues. - Excellent collaboration and communication skills in a cross-functional environment. Salary and Other Compensation: The annual salary for this position is between $70,000 to $117,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans. Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: - Medical/Dental/Vision/Life Insurance - Paid holidays plus Paid Time Off - 401(k) plan and contributions - Long-term/Short-term Disability - Paid Parental Leave - Employee Stock Purchase Plan Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law

• Define and maintain the enterprise data architecture blueprint, including data models, standards, and governance frameworks. • Align data architecture with business strategy by collaborating closely with business and IT stakeholders. • Design and oversee scalable data solutions across transactional, analytical, and streaming environments. • Establish standardized data integration and interoperability patterns across platforms. • Lead data platform modernization initiatives, including cloud adoption and migration. • Define and enforce data governance, data quality, metadata management, and MDM frameworks. • Provide architectural guidance, reviews, and mentoring to architects, data engineers, and delivery teams. • Partner with Security and Compliance teams to ensure data privacy and regulatory compliance.

Role Description Our client is a large, technology‑driven logistics and e‑commerce services organization operating at significant scale. The company processes high volumes of operational and analytical data daily and invests heavily in modern cloud‑based data platforms. Data is a critical enabler for business performance, decision‑making, and continuous optimization across the organization. You will join a Data Services / Data Engineering team responsible for designing, building, and operating scalable data solutions on a modern cloud analytics platform. The team supports multiple business domains by delivering reliable, well‑governed, and high‑performance data pipelines. You will be: - Designing, developing, and maintaining scalable data pipelines using Python and PySpark. - Building and operating Delta Live Tables pipelines in both streaming and triggered modes. - Selecting and configuring appropriate Databricks compute for different workload types. - Implementing and maintaining data governance using Unity Catalog across Databricks workspaces. - Diagnosing, analysing, and optimising slow SQL queries on large Delta tables. - Defining, packaging, and deploying Databricks resources using Databricks Asset Bundles. - Collaborating closely with other data engineers, analytics teams, and platform stakeholders. - Contributing to best practices around performance, reliability, and maintainability of data solutions. Qualifications - Strong experience with AWS Databricks. - Proven experience building scalable data pipelines using Python and PySpark. - Hands‑on experience designing and operating Delta Live Tables pipelines. - Solid understanding of Databricks compute options and the ability to choose the right configuration for specific workloads. - Ability to diagnose and optimise slow SQL queries on large Delta tables using a structured approach. - Experience using Databricks Asset Bundles for infrastructure and deployment as code. - Experience working with Unity Catalog to centralize data governance. - Experience working in complex, data‑intensive environments with large datasets. - Good understanding of data modeling and data quality concepts. - Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. - Work from the European Union region and a work permit are required. Requirements - Familiarity with CI/CD practices for data platforms. - Experience collaborating in cross‑functional, agile teams. - Experience with streaming data architectures. - Exposure to data platform cost optimization. - Experience mentoring or supporting other data engineers. - Knowledge of wider AWS data ecosystem services. - Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work. - Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. Recruitment Process - CV review - HR call - Interview - Client Interview - Decision