Senior Data Warehouse And Integration Engineer Jobs

About Goods & Services Goods & Services is a product design and engineering company. We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services . Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size. Headquartered in the United States , we operate regional development centers in Mexico and the United Kingdom . This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect. At Goods and Services, we value diversity and are committed to creating an inclusive workplace where everyone can thrive. We are proud to be an Equal Opportunity Employer and welcome qualified applicants from all backgrounds. About the job Goods & Services is looking for a Senior Data Warehouse and Integration Engineer responsible for database engineering, data warehouse architecture and support, data integration, reporting support, production troubleshooting, and technical delivery. This role requires someone who can independently own complex DB/data work from investigation and design through production completion and ongoing support. The biggest need is database/data integration ownership and production troubleshooting, followed by data warehouse architecture and reporting. The role needs someone to be comfortable with the existing on-prem/Microsoft environment while also helping us move toward more modern Azure-based solutions. What you’ll do: Design, develop, maintain, and troubleshoot SQL Server databases, stored procedures, views, jobs, and related database objects. Design and support enterprise data warehouse architecture, data models, schemas, and data flows. Evaluate and improve data warehouse structure, scalability, performance, and maintainability

We are looking for a Lead, Data Development, AI Platform to lead the team building and operating the technical platform behind Hootsuite's Analytics MCP. This includes routing infrastructure, orchestration services, agent infrastructure, and data pipelines that enable reliable AI-driven analysis at scale. You will set technical direction for the team, strengthen engineering practices, and translate target architecture and integration standards into secure, production-grade systems that Data Analytics & AI teams can confidently build on. This is a hands-on technical leadership role. You will stay close to the code while owning delivery outcomes, engineering quality, and the team's culture of craft and accountability. You will develop strong, well-reasoned recommendations on how the platform and orchestration architecture should evolve, seek approval at the Senior Manager and Director level, and then guide the team through disciplined execution. You will also partner closely with AI Context & Integration and AI Data Architecture to ensure the platform, context layer, semantic layer, and downstream agent workflows operate as one coherent system. WHAT YOU’LL DO: Lead the design and delivery of the orchestration layer that connects the Analytics MCP platform across its most complex surfaces, including query execution across schemas and models, federated data access between the data warehouse and external source systems, and multi-step agent workflows for cross-functional business processes. Develop clear technical recommendations for platform and orchestration architecture evolution, align those recommendations with Senior Manager and Director-level direction, and guide the team through disciplined execution within the approved architecture. Own the operational reliability, scalability, quality, and observability standards for core Analytics MCP components, including routing and agent infrastructure. Guide the team to build and operate these systems to prod

About the Role We are seeking an experienced Senior Data Engineer to join our growing Data & Analytics team. This role will be responsible for designing, developing and maintaining scalable data pipelines and infrastructure to support our organization’s data needs. Specific Responsibilities: Design, develop, and maintain robust data pipelines and infrastructure to support data integration, processing, and storage Collaborate with analysts and other stakeholders to understand data requirements and translate them into technical solutions Implement best practices for data governance, security, and quality assurance to ensure the reliability and accuracy of data Explore and evaluate new technologies and tools to enhance our data infrastructure and capabilities Design and implement complex data models on Azure Synapse Analytics to support data warehousing Utilize Azure DevOps for continuous integration, continuous delivery, and agile project management. Manage and optimize Apache Spark pools for high-performance data processing tasks. Develop and maintain ETL processes and data pipelines using Python scripting. Ensure data quality and integrity across all platforms and systems. Collaborate with cross-functional teams to translate business needs into technical specifications. Stay current with industry trends and advancements in Azure data services. What you'll need: Bachelor’s degree in Computer Science, Engineering, or related field Minimum of 5+ years experience in data engineering roles, with a strong focus on building and maintaining data pipelines and infrastructure Strong proficiency in Azure Synapse Analytics, Azure DevOps, and Apache Spark pools. Expertise in Python scripting and other programming languages such as SQL and Java Senior level knowledge of data modeling, processes, and data warehouse concepts Strong communication skills and ability to effectively communicate technical concepts to non-technical stakeholder

About the Role We are seeking a Staff Enterprise Architect, Data to lead the strategy, design, and modernization of our enterprise data landscape. This role operates at the intersection of data architecture, engineering, and AI enablement, defining solutions to integrate our Data Lake and Data Warehouse across multi-cloud platforms. Over the next 12-18 months, you will enable self-service data access and natural language query capabilities for business users. You will architect Master Data Management and data lineage frameworks ensuring AI models operate on high-quality, governed data. You will also evaluate and implement AI-powered tools to automate data quality monitoring and enhance data security. We're looking to speak with candidates based in the San Francisco Bay Area for our hybrid working model. Key Responsibilities Data Strategy & Roadmap Design semantic layer architecture standardizing business metrics enterprise-wide. Define governance guardrails ensuring natural language queries access validated master data sources Develop Master Data strategy for Customer and Product domains (phases 1-2), Finance and People to follow. Define golden record requirements, stewardship models, and system-of-record hierarchy. Partner with business owners on master data governance Define cross-cloud data integration strategy and reference architecture. Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data freshness. Document trade-offs and recommend implementations for batch and near-real-time use cases Develop 12-24 month data architecture roadmaps for Finance, Sales, Product, and People. Identify capability gaps and recommend technology investments with business value and effort estimates Systems Design & Solution Leadership Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure prediction, and data classification. Define requirements, lead vendor POCs, and establish integration patterns

As TaylorMade continues to grow, the number and complexity of integrations are increasing. TaylorMade maintains a substantial number of data interfaces across multiple time zones, operating 24/7, many involving multi-step processes and connecting several major global applications. This ecosystem requires continuous monitoring, support, and enhancement. The Senior Software Engineer, Integration is responsible for the ongoing improvement and evolution of TaylorMade’s enterprise application integration (EAI) environment, including supporting processes, procedures, and technologies. The successful candidate will demonstrate expertise in delivering modern, high-performing, and secure business software systems using cutting-edge technologies and tools, including middleware, iPaaS, and cloud-based databases. This position is responsible for designing and building best-in-class application integration architectures and interfaces, leveraging both real-time and batch integration patterns. Essential Functions and Key Responsibilities: Participate in all aspects of high-level planning, design, development, and deployment of data integrations. Lead middleware and application interface activities, utilizing a strong EAI background to develop solutions. Design and architect ETL solutions for on-premise to on-premise, on-premise to cloud, and cloud-to-cloud scenarios. Participate in technical discussions and provide guidance and expertise for Informatica and related middleware and data architecture technologies. Ensure all interfaces and middleware components perform as expected and are proactively monitored and managed for availability and capacity. Employ strong problem-solving skills and a proactive attitude, taking full ownership of assign

Who we are Artefact is a new generation of data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe. We have over 1500 employees across 20 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client. Job Summary We are looking for a Senior Data Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. Key Responsibilities Design, build, and maintain scalable and robust data pipelines using SQL, Python, Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark. Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms. Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing. Work closely with data architects, analysts, and other stakeholders to understand business requirements and translate them into technical implementations. Oversee and manage a team of data engineers, providing guidance and mentorship to ensure high-quality project delive

Senior Data Engineer Who we are Artefact is a new generation of data service provider, specialising in data consulting and data-driven digital marketing, dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. Our broad range of data-driven solutions in data consulting and digital marketing are designed to meet our clients’ specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we’ve acquired with our 1000+ client base around the globe. We have over 2000 employees across 26 offices who are focused on accelerating digital transformation. Thanks to a unique mix of company assets: State of the art data technologies, lean AI agile methodologies for fast delivery, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts, all dedicated to bringing extra value to every client. Job Summary We are looking for a Senior Data Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. Key Responsibilities Design, build, and maintain scalable and robust data pipelines using SQL and Python, and leveraging any of the following: Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark. Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms. Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing. Work closely with data architects, analysts, and other stakeholders to understand business requirements and translate them into technical implementations. Oversee and manage a team of data engineers, prov

The Data Architect plays a critical role in designing and building foundational data platforms that enable customers to move, organize, and analyze their business data at scale. In this position, you will partner with client team members to architect, implement, and deploy data warehouse solutions across multiple cloud platforms and customer organizations. This position requires deep expertise in medallion layer design, ELT implementation, semantic layer architecture and BI tool integration. You should be able to lead architecture discussions, guide technical execution, and mentor junior engineers. As a senior technical contributor, you will take ownership of complex data warehouse solutions, conduct technical discovery with customers, and ensure scalable, maintainable data architectures. You will act as a trusted technical advisor to both internal teams and customer stakeholders while driving best practices in data design, pipeline development, semantic layer modelling, and BI implementation. Responsibilities Design medallion layer data warehouse schemas (bronze, silver, gold) on Databricks, Redshift, Snowflake and/or BigQuery. Select and implement ELT tools to move data from source systems into the warehouse. You'll evaluate options, configure pipelines, and troubleshoot performance issues. Build and optimize semantic layers on top of the warehouse so analysts and business users can query data without writing SQL. Connect data warehouses to BI platforms (Tableau, Looker, Power BI, or similar) to enable self-service analytics and reporting. Translate business requirements into scalable technical integration architectures and implementation strategies. Facilitate discovery sessions and technical workshops with clients to understand system landscapes, integration requirements, and data flows. Own complex integration solutions from design through deployment, ensuring high performance, scalability, and maintainability. Advise on data governance, quality checks, and cos

JOIN OUR TEAM As a ( Senior) Product Manager , you will join our Technology team to drive the efficiency of Westwing's supply chain and fulfilment operations across Europe. Operating at the intersection of business and technology, you will partner with senior stakeholders to translate operational strategy into scalable systems across warehouse, order, and delivery management. Having recently completed a major migration of our order and warehouse management systems to modern SaaS platforms, we are now transitioning from initial stabilisation to building the next generation of scalable capabilities on top of that foundation. In this high-impact role, you will directly drive operational excellence and cost efficiency by shaping the systems that power our end-to-end processes, from initial sourcing to final customer delivery. This position is permanent and based in Munich . WHAT YOU'LL DO Partner with stakeholders across Sourcing, Logistics, Warehouse, and Operations to own the roadmap for our Supply Chain and Fulfilment systems, spanning both SaaS platforms and in-house tools Own and drive measurable business outcomes aligned with company OKRs and operational performance targets, translating operational needs into clear functional specifications and defining KPIs for data-led optimisation Coordinate the implementation of new and existing capabilities with our SaaS vendors and integration partners, driving delivery through to rollout Own the end-to-end product lifecycle for in-house operational tools, from prioritisation and delivery to continuous improvement, working closely with engineering, data, and design teams to ensure high-quality, scalable, and timely delivery Drive product discovery to identify automation and optimisation opportunities, leveraging AI and emerging technologies to innovate across the supply chain Make build-versus-buy decisions based on speed, scalability, and long-term impact, helping shape our evolving strategy across SaaS and in-house tooling

At Curai, we believe that access to high-quality healthcare is a fundamental human right, not a privilege. Our mission is to radically transform healthcare by harnessing the power of artificial intelligence and clinical expertise to make care more affordable, accessible, and effective for everyone. We are looking for a Senior Software Engineer, Marketing Platform, to build the systems that help people discover Curai Health and find care. You’ll own the web, measurement, and data integration systems to support marketing and growth. What You'll do as a Senior Software Engineer, Marketing Platform In a typical day in the life of a Curai Senior Software Engineer, you’ll: Turning priorities from marketing into scoped engineering projects Define funnel events, implement client and server side tracking, and reconcile conversion data with warehouse reporting. Build SQL models and dashboards to examine cost per visit and cohort behavior Support the build pipeline and ClickHouse data behind our MTA tooling Designing, building, and maintaining web features and the APIs and data flows supporting them Investigating site performance, conversion, and data quality issues, then shipping improvements Reviewing code, improving tests and monitoring, and making technical decisions with the broader engineering team What You'll Need We recognize not everyone will have all of these requirements. If you

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Digital Twin Platform team at Instacart is responsible for understanding exactly what is on store shelves at all times. Inventory estimates power some of the most important product experiences at Instacart, from search and advertising to logistics and fulfillment. We own the end-to-end data supply chain — from ingestion and integration of partner data sources to collecting inventory observations, to model development, serving, and integrations across our products. We are looking for a highly motivated Senior Software Engineer to join our team. You will be instrumental in building our next generation platforms for understanding where products are in a store — think: platforms that provide the precision and depth of a smart warehouse but scaled to every local store. In close collaboration with machine learning engineers, computer vision engineers, produc

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy. The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product. The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge. What you'll do Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model. Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI. Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working. Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge. Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.

Expression of Interest – Future Opportunities We’re building a pipeline of talented professionals interested in future opportunities with Artefact. This posting is for resume collection and does not represent an immediate vacancy. We welcome you to share your resume, and our recruiting team may reach out as opportunities aligned with your experience become available. Who We Are Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel. We have 2000 employees across 36 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe. Find out more at artefact.com . Our Opportunity We are looking for a Senior AI & Agentic Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment. Key Responsibilities Design, build, and maintain scalable and robust data pipelines using SQL, Python, Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark. Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms. Implement continuous integration and co

The Field CTO is the most senior technical voice in the field. Here's the version we're hiring for. The Field CTO sits a level above the Solution Architect. Where the SA leads the technical strategy on complex deals, the Field CTO owns the technical narrative across the territory, shapes how the market understands Sigma's architecture, and carries the credibility to win the room when the CTO, CDO, and CISO are all in it. This person does everything a senior SA does, then operates a tier higher: as a peer to enterprise executives, a force multiplier across the entire Solution Engineering team, and a direct line back into Product and Engineering. Three things sit at the center of this role. The Field CTO does all three at the highest level, with the architectural depth and executive presence to back it up. 1. Use AI every day, and set the standard for how the team uses it. The Field CTO treats AI tooling as default infrastructure and raises the bar for everyone else. You run Claude, ChatGPT, Cursor, or equivalents to compress account prep, architecture design, prototype builds, RFP responses, and discovery synthesis from weeks into days. You bring a clear point of view on what to run, why, and where it breaks. You don't just use these tools well. You teach the SE and SA teams how to use them better, and you build the workflows the rest of the field adopts. 2. Sell AI into the account at the executive level. Buyers want to talk about agents, MCP, A2A, context engineering, and which model powers what. You're fluent, and you can take that conversation to the most senior technical buyer in the building. You know Sigma's AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, Sigma agents, and warehouse agents. You architect these into a customer's stack, defend the tradeoffs to a head of data and a CISO in the same call, and frame the long-term AI strategy for a CTO who's deciding w

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an