Software Gigs

Own end-to-end demand forecasting and capacity planning for AI systems, compute, storage, GPU, and emulation across a global engineering organization spanning tens of thousands of servers and hundreds of petabytes of storage. Translate silicon product roadmaps and tapeout schedules into multi-year demand plans, size and justify capital purchases into the hundreds of millions of dollars, and present capacity positions to engineering and finance leadership. Build and maintain forecasting models, decision rules, and utilization analytics; apply AI and automation to move beyond manual spreadsheet work. Lead and mentor a team of analysts, raising their craft and setting analytical direction.

As Principal Software Engineer for AI & Data Platform, you will architect the data foundation for scientific and engineering R&D platforms, designing scalable data processing patterns, ML training pipelines, and intelligent workflow interfaces. You will own end-to-end responsibilities including data modeling for multi-use analytics and ML, building production training and fine-tuning pipelines, model evaluation and benchmarking, and setting engineering standards for the team. The role requires 10+ years shipping production software, expert-level Python, deep experience with large-scale data systems (object storage, analytical processing, training formats), hands-on ML pipeline development, and the ability to set technical direction in early-stage environments while implementing it yourself.

Staff Software Engineer leading design and evolution of PlayStation's Real-Time Analytics Platform (RTAP), a large-scale distributed data system handling high-throughput, low-latency analytics and stream processing. Responsibilities include architecting stream processing pipelines, optimizing data services using Apache Flink, Spark, ClickHouse, and Druid, integrating batch and streaming workloads with lakehouse architectures, and building AI-powered capabilities for platform automation. The role requires deep expertise in distributed systems, real-time analytics, and mentoring engineering teams while establishing technical standards and best practices across the organization.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, integration patterns, and architectural standards for the Data Lake, Data Warehouse, ODS, and cloud platforms while ensuring security, resilience, and high performance. Working closely with engineering, analytics, and business teams, the architect provides technical guidance on modern data systems, governance frameworks, and ETL/ELT pipelines. The position combines strategic vision with practical experience optimizing structured, semi-structured, and unstructured workloads across SQL, NoSQL, and cloud-native systems.

Staff-level engineer designing and operating large-scale distributed data platforms powering real-time analytics across PlayStation. You will lead the architecture and evolution of the Real-Time Analytics Platform (RTAP), own critical capabilities end-to-end from design through production operations, and mentor engineers. Key responsibilities include building and optimizing distributed services using Apache Flink, Spark Structured Streaming, ClickHouse, and Apache Druid; integrating batch and streaming workloads with lakehouse architectures; and establishing technical standards for distributed systems, stream processing, and data modeling.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, cloud-native integration patterns, and architectural standards supporting analytics, reporting, and digital banking applications. This position combines strategic architectural vision with practical expertise in designing, implementing, and optimizing modern data systems across structured, semi-structured, and unstructured workloads. The architect provides technical leadership to Data Engineers and cross-functional teams while ensuring secure, resilient, and high-performing data environments.

Lead day-to-day technical project delivery for Distribution Operations initiatives including outage management, solar/battery data integrations, forecasting, automation, and analytics. Transform technical requirements into delivery plans, sprint backlogs, and release milestones while coordinating work across data engineers, architects, cybersecurity teams, and vendors. Manage project controls, scheduling, defect tracking, and comprehensive documentation across integrations, ETL/ELT pipelines, cloud analytics, and Power Platform solutions. Facilitate design reviews, support operational readiness, and ensure technical solutions meet engineering rigor and real-world operational needs.

As Senior Manager of AI Governance Technology at Teradata, you will own the end-to-end technical architecture of the company's AI Governance Operating System, including intake pipelines, compliance monitoring, and agentic workflows. You'll lead the engineering of sophisticated automation using tools like n8n and Claude APIs, architect the AI tool registry, and design real-time monitoring systems that anticipate governance challenges. You'll serve as the internal expert on Claude Enterprise, Microsoft Copilot, and Teradata AI Studio integrations, setting technical standards and specifications that guide the broader engineering team. This is a technical leadership role requiring deep expertise in enterprise AI governance, system architecture, and the ability to make complex engineering decisions with significant autonomy.

Design, build, and scale ETL/ELT pipelines and cloud data warehouse infrastructure using Python, SQL, and modern orchestration tools like Apache Airflow or Prefect. Own the end-to-end data infrastructure that powers business intelligence and operational reporting, including data quality checks, anomaly detection, and performance optimization. Collaborate with analytics and software engineering teams to define data modeling standards and maintain infrastructure-as-code deployments using Terraform and CI/CD. Requires 3–6 years of data engineering or backend development experience with advanced SQL, Python, and hands-on work with cloud data warehouses like Snowflake or BigQuery.

Senior Database Engineer II will build and maintain scalable data pipelines using Azure Data Factory, Databricks, Azure Synapse Analytics, and Snowflake. The role requires designing and implementing conceptual, logical, and physical data models, leading system integration efforts, and architecting multi-tenant database solutions for the medical device industry. You'll provide technical leadership on data engineering standards, conduct code and design reviews, and collaborate across geographically dispersed teams in an Agile environment. The position demands 7+ years of database design and software development experience, with a strong focus on healthcare compliance and data governance.

Design and develop advanced Power BI dashboards using DAX, Power Query, and complex data modeling techniques. Consolidate and transform data from APIs, files, and SQL databases into reliable reporting models using ETL workflows with SSIS and T-SQL. Build scalable reporting solutions and partner with business users to translate requirements into technical implementations in a fast-paced, multi-project environment. Requires 3+ years of hands-on experience with DAX, Power Query, T-SQL, SSIS, and strong SQL development skills including stored procedures and query optimization.

The Mid-Level Power Platform Developer will design, build, and enhance enterprise solutions using Microsoft Power Apps (Canvas and Model-Driven), Power Automate, and Dataverse. Responsibilities include developing automated workflows, optimizing data models, integrating with external systems via custom connectors and REST APIs, and ensuring solutions meet enterprise governance and security standards. The role requires 2–5 years of Power Platform experience, proficiency in app development and cloud flows, strong Dataverse knowledge, and familiarity with solution packaging and ALM concepts.

Design, build, and maintain enterprise data pipelines using Microsoft Fabric and Azure Synapse, handling ingestion, transformation, and orchestration from ERP and supply chain systems. Develop and manage Fabric Lakehouse and Warehouse architectures, apply data modeling best practices, and ensure data quality and reliability. Collaborate with analytics, BI, and IT teams to create governed, scalable analytical data assets that support Power BI and downstream consumers. Requires a bachelor's degree in a quantitative field, strong SQL and Python skills, and hands-on experience with Microsoft Fabric and Azure Synapse.

Data Engineer II will maintain and enhance data infrastructure, pipelines, and models supporting manufacturing analytics and operational reporting at Dexcom. The role involves writing and optimizing SQL queries, supporting ETL/ELT pipeline development in BigQuery using tools like Google Cloud Dataflow, Apache Beam, and dbt, and troubleshooting data quality issues. You will partner with business stakeholders to gather requirements, document data lineage and workflows, and develop foundational GCP cloud engineering skills. The ideal candidate has a technical degree or equivalent experience and enjoys solving practical operational problems while learning modern cloud data practices.