Data Engineer AI
Minto, AK · On-site +1
$118K - $142K/yr
A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office. #LI-TS1 #remote Sedgwickis an Equal ...
Data Engineer AI
Minto, AK · On-site +1
$118K - $142K/yr
A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office. #LI-TS1 #remote Sedgwickis an Equal ...
Data Engineer AI
Minto, AK · On-site +1
$118K - $142K/yr
A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office. #LI-TS1 #remote Sedgwickis an Equal ...
Data Engineer AI
Minto, AK · On-site +1
$118K - $142K/yr
A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office. #LI-TS1 #remote Sedgwickis an Equal ...
Remote Teradata information
What are the key skills and qualifications needed to thrive as a Remote Teradata professional, and why are they important?
To thrive as a Remote Teradata professional, you need a strong background in database management, SQL programming, and data warehousing concepts, often supported by a degree in computer science or a related field. Familiarity with Teradata tools, data integration platforms, and certifications such as Teradata Certified Professional are commonly required. Excellent problem-solving, communication, and self-motivation are crucial soft skills for effective remote collaboration and troubleshooting. These skills ensure efficient data management, seamless teamwork, and the ability to deliver solutions in distributed work environments.
How do Remote Teradata professionals typically collaborate with on-site teams and stakeholders?
Remote Teradata professionals often use a combination of video conferencing, instant messaging, and project management platforms to maintain close communication with on-site teams. They frequently participate in regular meetings to discuss project progress, troubleshoot issues, and align on database management strategies. Collaboration is essential, especially when working on large-scale data warehousing solutions, so remote professionals are expected to be proactive in providing updates and sharing insights. Clear documentation and consistent communication help bridge the gap between remote and on-site teams, ensuring seamless integration and efficient project delivery.
What is the difference between Remote Teradata vs Remote SQL Developer?
| Aspect | Remote Teradata | Remote SQL Developer |
|---|---|---|
| Required Credentials | Teradata certifications, SQL knowledge | SQL certifications, database knowledge |
| Work Environment | Data warehousing, large-scale enterprise systems | Application development, database management |
| Industry Usage | Data analytics, telecom, finance | Software, finance, healthcare |
| Common Search/Comparison | Yes | Yes |
Remote Teradata professionals focus on managing and optimizing Teradata data warehouses, requiring specific Teradata certifications and experience with large-scale data systems. Remote SQL Developers work across various databases, including SQL Server, MySQL, and PostgreSQL, often with broader application development skills. While both roles involve SQL expertise, Remote Teradata roles are more specialized in data warehousing, whereas Remote SQL Developers have a wider scope in database and application development.
What are Remote Teradata jobs?
Remote Teradata jobs are positions that involve working with Teradata, a leading data warehousing and analytics platform, from a location outside the traditional office environment. These roles typically include responsibilities such as database administration, development, data analysis, and system maintenance, all performed remotely. Remote Teradata professionals use secure connections to access company systems, enabling them to manage large datasets, optimize queries, and support business intelligence initiatives from anywhere. This flexibility allows companies to hire talent from a broader geographic area while also giving employees a better work-life balance.
What are popular job titles related to Remote Teradata jobs in Alaska? For Remote Teradata jobs in Alaska, the most frequently searched job titles are:
What job categories do people searching Remote Teradata jobs in Alaska look for? The top searched job categories for Remote Teradata jobs in Alaska are:
Sedgwick rating
7.6
Based on 314 frontline employees who took The Breakroom Quiz
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Job description
By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.
Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies
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Data Engineer AIRole Overview
As a Senior Data Engineer within the Transformation Office, you are the hands-on architect of the data supply chain for our most advanced initiatives. You will be responsible for the "heavy lifting" required to fuel Data Science models and AI applications with high-fidelity data. Your mission is to build the pipelines that bridge our legacy on-prem systems (Mainframes, SQL Server, DB2) with our modern Snowflake environment and AWS/Azure AI stacks. You are a "day-one" builder who ensures that data is not just moved, but engineered for the specific requirements of model training, feature stores, and RAG-based AI systems.
Key Responsibilities
Hybrid Data Pipeline Execution: Design and implement robust ETL/ELT pipelines to ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL), centralizing it for consumption in Snowflake and AI services.
Engineering for Data Science: Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring Data Scientists have immediate access to clean, versioned, and statistically valid data.
Engineering for AI (RAG & LLMs): Develop the data pipelines required for Generative AI, including the automated extraction, chunking, and loading of unstructured data into vector stores across AWS and Azure.
Snowflake Power-User Execution: Act as the technical lead for our Snowflake data warehouse, implementing sophisticated data modeling, Snowpipe automation, and compute optimization to support high-concurrency AI workloads.
Legacy "Back-Reach" Engineering: Execute non-invasive data extraction patterns to unlock mission-critical data from decades-old on-premise systems without disrupting core business operations.
Multi-Cloud Orchestration: Manage complex, cross-platform data workflows using Airflow, Step Functions, or Azure Data Factory, ensuring the synchronization of data across our multi-cloud AI posture.
IT & Security Diplomacy: Partner directly with central IT, Database Administrators, and Security teams to solve connectivity hurdles (PrivateLink, IAM, firewalls) and secure "license to operate" for new data flows.
Data Quality for Model Integrity: Implement automated validation and observability layers to detect data drift and quality issues that could compromise the accuracy of production AI and Data Science models.
Cost & Performance Management: Drive the efficiency of our data stack by optimizing storage and query performance in Snowflake, AWS, and Azure to manage the ROI of the Transformation Office.
Direct Stakeholder Collaboration: Work as a dedicated engineering partner to MLOps and Data Science teams to rapidly iterate on data requirements for evolving AI use cases.
Qualifications
Education: Bachelor's degree in Computer Science, Data Engineering, or a related field is required. A Master's degree is highly desirable.
Proven Execution: 6+ years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments.
Snowflake Mastery: Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI services.
Multi-Cloud Proficiency: Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services.
Technical Stack: Mastery of Python, SQL, and PySpark. Deep experience with data orchestration and containerization (Docker).
Legacy Expertise: Proven ability to interface with "old world" tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumption.
AI/DS Fluency: A strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines).
Execution Mindset: A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office.
#LI-TS1 #remote
Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace.
If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.