The Life Data Platform team is responsible for acquiring, integrating, governing, modeling, and publishing enterprise data across on-premises and cloud platforms. The Associate Data Engineer will support the design, development, and maintenance of data pipelines, data models, and enterprise data products.
Responsibilities
Develop, maintain, and support scalable data pipelines and data integration solutions.
Assist in building and supporting enterprise data products for reporting, analytics, and operational use cases.
Develop and maintain data models, data warehouses, and dimensional modeling solutions with guidance from senior team members.
Integrate data from internal systems, cloud platforms, APIs, and third-party vendors.
Partner with stakeholders to understand business requirements and translate them into technical solutions.
Requirements
Bachelor's degree in a technical, engineering, quantitative, or related discipline
Nice to have: AWS ecosystem experience
Nice to have: Dremio
Nice to have: Data Catalog technologies
Nice to have: Experience supporting analytical and operational data products
This role leads the design, execution, and continuous improvement of enterprise-wide data operations processes that ensure the reliability, quality, and accessibility of data supporting T-Ads business decisions. It serves as the senior technical authority for data integrations, pipeline automation, and governance across on-premises and multi-cloud environments.
Compensation
Total Target Cash Opportunity: $112,930 - $225,860. National Base Pay Range: $98,200 - $196,400
Responsibilities
Own and continuously enhance enterprise data operations frameworks, service-level standards, and escalation processes spanning data integration, pipeline automation, billing, file transfer, and governance across on-premises and multi-cloud environments (Azure, AWS, Google Cloud).
Serve as the senior technical authority and escalation point for complex data quality, integration, and pipeline issues, building and maintaining infrastructure across tools including Snowflake, AWS Lambda, S3, and Streamlit.
Lead migration of manually-maintained processes to fully automated, documented systems — eliminating single points of failure and driving self-service capabilities for data refresh, reporting, and dashboard processes.
Manage data partner and vendor relationships, ensuring adherence to SLAs, contract terms, and performance standards for data tools and platforms.
Drive data governance standards and international data expansion efforts across partner integrations.
Seeking a Software Engineer II to build and maintain data-centric platforms and shape the next generation of enterprise data capabilities, evolving from data engineering toward platform engineering.
Compensation
Arlington, Virginia: $106,000 - $169,000 USD
Responsibilities
Design, build, and maintain scalable data-centric platforms, services, and integrations across cloud and on-premises environments.
Contribute to the development of a new enterprise data platform while supporting and enhancing the existing data movement platform.
Develop and optimize data-intensive applications using Spark, Databricks, and related technologies to process, transform, and serve data efficiently.
Build backend services and APIs that support data onboarding, exchange, discovery, and consumption capabilities.
Write clean, maintainable, and well-tested code, and contribute to code reviews, CI/CD practices, and engineering standards.
Designing, building, and maintaining scalable data pipelines, integrations, and reusable data services that enable enterprise AI, analytics, and data initiatives.
Compensation
C$80 to C$95
Responsibilities
Design, develop, test, and maintain ETL/ELT pipelines and data integration solutions across enterprise data sources.
Build reusable data pipelines, services, and integration components that can support multiple AI and analytics use cases.
Ingest, transform, and prepare structured and unstructured data for analytics, AI, and machine learning workloads.
Implement data architecture, modeling, and integration patterns established by enterprise architecture.
Integrate data across cloud platforms, databases, applications, APIs, and enterprise systems.
Requirements
Degree in Computer Science, Information Systems, Engineering, Data/Analytics, or a related discipline, or equivalent experience
Lead the architecture strategy, governance, and execution model for Post’s enterprise capabilities, focusing on integration platforms, AI-enabled automation, and scalable technology patterns.
Responsibilities
Lead architecture strategy and governance for enterprise and shared services
Develop and recommend strategic roadmaps for AI, integration, and automation
Assess emerging technologies and recommend investment
Establish architecture best practices and governance forums
Lead technology initiatives for corporate platforms
Requirements
Bachelor’s or master’s degree in business administration, Information Technology, or related field
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