data transcriber

Ad Astra, Inc.

<div>Job Type: Contract / Freelance
Work Location: Remote (U.S.-Based) 
 
 
 
About the Opportunity
Ad Astra is currently seeking bilingual Spanish-English transcriptionists to support ongoing federal and government-related projects.
We are looking for linguists who are comfortable working with spoken Spanish content and producing accurate English-language transcripts while maintaining high quality standards and confidentiality.
Projects may involve legal, financial, government, and administrative subject matter. 
 
 
Responsibilities
<ul><li>Transcribe Spanish-language audio into English
</li><li>Accurately identify multiple speakers
</li><li>Follow client-specific formatting and transcription guidelines
</li><li>Meet project deadlines
</li>Complete required certifications and project documentation when applicable 
<li>
</li></ul> 
 
 
Requirements
<ul><li>Must be based in the United States
</li><li>Professional proficiency in Spanish and English
</li><li>Strong English writing skills
</li><li>Ability to accurately understand and transcribe spoken Spanish
</li><li>Comfortable working with legal, financial, and government-related content
</li><li>Experience with transcription and/or translation preferred
</li>Experience with multi-speaker recordings is a plus 
<li>
</li></ul> 
 
Additional Information
<ul><li>Freelance / contractor opportunity
</li><li>Remote work
</li><li>Ongoing project needs
</li><li>Federal and government-related assignments
</li><li>Long-term collaboration opportunities available</li></ul></div>
 At Ad Astra, we don't just break language barriers, we shatter them! Our team of language professionals speaks, signs, and writes in over 250 languages, helping companies connect with consumers all over the world. As a woman-owned small business, we're proud of our long-standing reputation for providing unparalleled language services to clients across the nation and globe.
 Transcription

US-Based English-Spanish Transcriptionist | Federal Projects

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

DOHA BANK

<div>
 
 
 Role Summary
 
 
 
 The Data Steward is responsible for ensuring the accuracy, integrity, and governance of enterprise data assets by executing data governance policies and managing data quality at an operational level.
 
 
 
 
 
 This role acts as the primary custodian of data within assigned domains, ensuring data is consistent, compliant, and trusted across business functions, while collaborating closely with the Data Governance Officer and escalating critical risks to senior management.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Act as the primary owner of data quality and data definitions for assigned data domains
 </li>
 <li>
 Execute and enforce enterprise data governance policies in collaboration with the Data Governance Officer
 </li>
 <li>
 Maintain and update business glossaries, data definitions, and data rules in the enterprise data catalog
 </li>
 <li>
 Define, monitor, and validate data quality thresholds and data profiling outputs
 </li>
 <li>
 Investigate data issues, perform root cause analysis, and drive remediation and long-term fixes
 </li>
 <li>
 Ensure alignment between business data logic and technical data lineage across systems
 </li>
 <li>
 Review and enforce compliance with data governance and data handling policies across business units
 </li>
 <li>
 Identify, escalate, and track data risks, systemic issues, and non-compliance for management visibility
 </li>
 <li>
 Manage and approve data access requests in accordance with the principle of least privilege
 </li>
 <li>
 Assess the impact of system, process, or application changes on data quality, integrity, and reporting
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 5+ years of experience in data management
 </li>
 <li>
 2+ years of experience in data governance, preferably within banking or financial services
 </li>
 <li>
 Strong understanding of data quality management, metadata, and governance processes
 </li>
 <li>
 Good understanding of data flows, lineage, and business processes
 </li>
 <li>
 Experience with data cataloging and data quality tools
 </li>
 <li>
 Strong analytical and problem-solving skills, particularly in root cause analysis
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Data Science, Information Systems, Business Administration, or a related field
 </li>
 <li>
 Data governance certifications (e.g., CDMP, DCAM) are preferred
 </li>
 </ul>
</div>

Data Steward

TAWANTECH

<div>We are seeking a Data Modeler / Big Data Engineer to design scalable data architectures and support the bank&rsquo;s enterprise data platform, analytics, and digital transformation initiatives.
Key Responsibilities<ul><li>
Design and maintain enterprise data models for banking data domains.</li><li>
Develop and manage Data Lake and Big Data environments.</li><li>
Build scalable data solutions using Cloudera and Hadoop ecosystems.</li><li>
Implement and manage Apache Iceberg tables and data architectures.</li><li>
Support data governance, metadata management, and data quality initiatives.</li><li>
Collaborate with data engineering, analytics, and business teams.</li><li>
Optimize data performance and scalability.</li></ul> 

Requirements 
<ul><li>
5+ years of experience in data modeling and big data engineering.</li><li>
Strong knowledge of Cloudera Data Platform (CDP).</li><li>
Experience with Hadoop ecosystem technologies (Hive, HDFS, Spark, Impala).</li><li>
Hands-on experience with Data Lakes and Apache Iceberg.</li><li>
Strong SQL and data modeling skills.</li><li>
Experience with enterprise data architecture and governance frameworks.</li></ul>
Preferred Qualifications<ul><li>
Banking or Financial Services experience.</li><li>
Experience supporting enterprise data warehouse modernization initiatives.</li><li>
Knowledge of cloud-based data platforms and modern lakehouse architectures.</li></ul></div>

Data Modeler / Big Data Engineer

Dicetek LLC

<div>
 We are looking for a detail-oriented and analytical Business Analyst with strong expertise in data modelling tools such as Erwin, ER Studio, and equivalent platforms. The ideal candidate will bridge business requirements and technical solutions by translating complex data needs into structured models, ensuring data accuracy, consistency, and quality across systems.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Gather, analyze, and document business requirements from stakeholders.
 </li>
 <li>
 Translate business needs into logical and physical data models.
 </li>
 <li>
 Design and maintain data models using Erwin, ER Studio, or similar tools.
 </li>
 <li>
 Collaborate with data architects, developers, and business teams to ensure alignment.
 </li>
 <li>
 Perform data analysis, data mapping, and data lineage documentation.
 </li>
 <li>
 Ensure data integrity, normalization, and standardization across systems.
 </li>
 <li>
 Support data governance and data quality initiatives.
 </li>
 <li>
 Create and maintain data dictionaries, ER diagrams, and metadata repositories.
 </li>
 <li>
 Identify process improvement opportunities and recommend data-driven solutions.
 </li>
 <li>
 Assist in UAT (User Acceptance Testing) and validate data-related requirements.
 </li>
 <li>
 Provide insights through reporting and data analysis to support decision-making.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in information technology, Computer Science, Business Administration, or a related field.
 </li>
 <li>
 3&ndash;8 years of experience as a Business Analyst, preferably in data-centric roles.
 
 
 </li>
 </ul>
 
 Hands-on Experience With
 
 
 
 <ul>
 <li>
 Erwin Data Modeler
 </li>
 <li>
 ER Studio
 </li>
 <li>
 Other data modelling tools (e.g., PowerDesigner, Oracle SQL Developer Data Modeler)
 
 
 </li>
 </ul>
 
 Strong Understanding Of
 
 
 
 <ul>
 <li>
 Data Modelling (conceptual, logical, physical)
 </li>
 <li>
 Database design principles
 </li>
 <li>
 ER diagrams and normalization techniques
 </li>
 <li>
 Proficiency in SQL for data analysis.
 </li>
 <li>
 Experience in data mapping, ETL processes, and metadata management.
 </li>
 <li>
 Familiarity with data governance frameworks and data quality tools.
 </li>
 </ul>
</div>

Business Analyst- Data Modelling & Architecture

RATP Dev

<div><h2 class="jobSectionHeader">Operations Data &amp; Investigation Supervisor</h2><div><ul><li><div>
Fixed-term contract</div></li><li><div>
Full-time</div></li><li><div>
At least 5 years of experience (Senior level)</div></li><li><div>
Bachelor degree</div></li><li><div>
Engineering/Maintenance Manager/Expert</div></li></ul></div></div>
 <div><div><div><div><div>Operations Data &amp; Investigation Supervisor</div></div><div><h2 class="jobSectionHeader">
Mission
</h2><div>JOB PURPOSE:
The Operations Data &amp; Investigations Supervisor is responsible for overseeing daily data analytics activities to support operational efficiency and business decision-making. The role involves managing the development of data standards, deploying automation tools, supervising the construction and analysis of datasets, and ensuring data is clean, accurate, and actionable. This position plays a critical role in transforming raw data into strategic insights through statistical analysis, visualization, and cross-departmental collaboration to inform investigations and operational improvements.</div></div><div><h2 class="jobSectionHeader">
Profile
</h2><div>RESPONSIBILITIES/DUTIES Data Analytics Oversight<ul><li>Supervise daily data analytics operations to ensure timely and accurate delivery of datasets that inform operational and business strategies.</li><li>Oversee the construction of data sets to support trend analysis, strategic insights, and informed decision-making across the organization.</li><li>Lead efforts to build processing capacity and develop team capabilities in statistical modeling, analytical methodologies, and data interpretation. Data Standards and Automation</li><li>Develop and implement data standards to ensure consistency, reliability, and integrity of data used in operational analysis.</li><li>Deploy and manage automation tools for efficient extraction, transformation, and loading (ETL) of data from various internal and external sources.</li></ul>
Data Preparation and Analysis<ul><li>Manage the data cleaning and preparation process, including filtering, managing missing data, and formatting datasets for accurate analysis.</li><li>Conduct data exploration and statistical analysis to uncover patterns, relationships, and emerging trends that support continuous improvement initiatives. Data Visualization and Reporting</li><li>Create visual representations of data insights through charts, graphs, and dashboards to enhance data comprehension and stakeholder engagement.</li><li>Prepare clear and concise reports and presentations that translate complex data findings into actionable recommendations for decision-makers. Cross-Functional Collaboration</li><li>Collaborate with various departments to understand their data needs, translate business requirements into analytical solutions, and support data-driven decision-making.</li><li>Act as a key liaison between operations, investigations, and business units to ensure data analytics efforts align with organizational objectives.</li></ul>
ESSENTIAL QUALIFICATIONS, KNOWLEDGE &amp; EXPERIENCE QUALIFICATIONS:<ul><li>Bachelor&rsquo;s degree in Engineering, Computer Engineering, or a related field.</li><li>High proficiency in English (spoken and written) is required. KNOWLEDGE:</li><li>Solid foundation in statistics and data interpretation.</li><li>Proficient in tools such as Excel, SPSS, SAS, Power BI, Tableau, and SQL.</li><li>Skilled in data analysis languages (e.g., Python, R).</li><li>Familiar with data preparation techniques, including cleaning and handling missing values.</li><li>Understanding of basic machine learning concepts for predictive analysis.</li><li>Capable of developing dashboards and reports for business insights.</li><li>Experienced with database systems and data visualization best practices. EXPERIENCE:</li><li>3 to 5 years of relevant experience in data analytics, or operations analysis, preferably within a supervisory or coordination role.</li></ul>
DESIRED BEHAVIORS &amp; EXPERIENCES<ul><li>Analytical Mindset: Approaches problems with data-driven thinking, using evidence and analysis to guide decisions.</li><li>Attention to Detail: Ensures data accuracy, quality, and completeness in all stages of analysis and reporting.</li><li>Proactive Leadership: Anticipates challenges in data management and takes initiative to improve processes and tools.</li><li>Effective Communicator: Clearly conveys complex data insights through visualizations, reports, and presentations tailored to various stakeholders.</li><li>Collaborative Attitude: Works closely with different teams to understand their needs and provide actionable data support.</li><li>Adaptability: Responds flexibly to shifting priorities, data demands, and evolving business requirements.</li><li>Integrity and Confidentiality: Handles sensitive data with professionalism, ensuring ethical standards and data privacy are maintained.</li><li>Continuous Improvement: Seeks opportunities to enhance data analytics capabilities and adopt best practices in tools, methods, and technologies.</li></ul></div></div></div></div><div><div><div><h3 class="jobSectionHeader"> 
Location</h3><div><div><div>
Location</div></div><div>
Address</div></div>
2 El Hegaz St, &Eacute;gypte</div></div></div></div><div></div>

Operations Data & Investigation Supervisor

<div>
 
 Introduction
 
 
 
 A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You&rsquo;ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you&rsquo;ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You&rsquo;ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
 
 
 
 Your Role And Responsibilities
 
 
 
 As a seasoned Data Engineer specializing in Data Integration, you will design and build solutions to transfer data from operational and external environments to the business intelligence environment. Your expertise will ensure the seamless flow of data throughout the business intelligence solution's lifecycle. Your primary responsibilities will include:
 
 
 <ul>
 <li>
 Design Data Integration Solutions: Create and implement Extract, Transform, and Load (ETL) processes to facilitate data transfer between environments, utilizing tools such as Informatica, Ab Initio software, and DataStage.
 </li>
 <li>
 Develop ETL Processes: Build and maintain efficient ETL processes to ensure accurate and timely data flow, adhering to best practices and industry standards.
 </li>
 <li>
 Implement Data Integration Tools: Utilize IBM's WebSphere Data Integration Suite to integrate data from various sources, ensuring data consistency and integrity.
 </li>
 <li>
 Ensure Seamless Data Flow: Monitor and troubleshoot data integration issues, collaborating with stakeholders to resolve problems and optimize data flow.
 </li>
 <li>
 Optimize Data Integration Solutions: Continuously evaluate and improve data integration solutions, identifying opportunities for process improvements and efficiency gains.
 
 
 </li>
 </ul>
 
 Required Technical And Professional Expertise
 
 
 
 <ul>
 <li>
 Data Integration Solution Design: Experience with designing and building solutions to transfer data from operational and external environments to the business intelligence environment, utilizing tools such as Informatica, Ab Initio software, and DataStage.
 </li>
 <li>
 ETL Process Development: Experience in creating and implementing Extract, Transform, and Load (ETL) processes to facilitate data transfer between environments, adhering to best practices and industry standards.
 </li>
 <li>
 Data Integration Tool Implementation: Experience with utilizing IBM's WebSphere Data Integration Suite to integrate data from various sources, ensuring data consistency and integrity.
 </li>
 <li>
 Data Flow Optimization: Experience in monitoring and troubleshooting data integration issues, collaborating with stakeholders to resolve problems and optimize data flow.
 </li>
 <li>
 Data Integration Solution Evaluation: Experience in continuously evaluating and improving data integration solutions, identifying opportunities for process improvements and efficiency gains.
 
 
 </li>
 </ul>
 
 Preferred Technical And Professional Experience
 
 
 
 <ul>
 <li>
 Data Integration Tool Expertise: Experience with utilizing IBM's WebSphere Data Integration Suite, Informatica, Ab Initio software, and DataStage to integrate data from various sources, ensuring data consistency and integrity.
 </li>
 <li>
 ETL Process Optimization: Experience in optimizing ETL processes to ensure accurate and timely data flow, adhering to best practices and industry standards.
 </li>
 <li>
 Data Flow Troubleshooting: Experience in monitoring and troubleshooting data integration issues, collaborating with stakeholders to resolve problems and optimize data flow.
 </li>
 </ul>
</div>

Senior Data Engineer - Data Integration

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