Job Title: Data Engineer Position Type: Full-Time, Remote Working Hours: U.S. client business hours (with flexibility for pipeline monitoring and data refresh cycles) About the Role: Our client is seeking a Data Engineer to design, build, and maintain reliable data pipelines and infrastructure that deliver clean, accessible, and actionable data. This role requires strong software engineering fundamentals, experience with modern data stacks, and an eye for quality and scalability. The Data Engineer ensures data flows seamlessly from source systems to warehouses and BI tools, powering decision-making across the business. Responsibilities: Pipeline Development: - Build and maintain ETL/ELT pipelines using Python, SQL, or Scala. - Orchestrate workflows with Airflow, Prefect, Dagster, or Luigi. - Ingest structured and unstructured data from APIs, SaaS platforms, relational databases, and streaming sources. Data Warehousing: - Manage data warehouses (Snowflake, BigQuery, Redshift). - Design schemas (star/snowflake) optimized for analytics. - Implement partitioning, clustering, and query performance tuning. Data Quality & Governance: - Implement validation checks, anomaly detection, and logging for data integrity. - Enforce naming conventions, lineage tracking, and documentation (dbt, Great Expectations). - Maintain compliance with GDPR, HIPAA, or industry-specific regulations. Streaming & Real-Time Data: - Develop and monitor streaming pipelines with Kafka, Kinesis, or Pub/Sub. - Ensure low-latency ingestion for time-sensitive use cases. Collaboration: - Partner with analysts and data scientists to provide curated, reliable datasets. - Support BI teams in building dashboards (Tableau, Looker, Power BI). - Document data models and pipelines for knowledge transfer. Infrastructure & DevOps: - Containerize data services with Docker and orchestrate in Kubernetes. - Automate deployments via CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI). - Manage cloud infrastructure using Terraform or CloudFormation. What Makes You a Perfect Fit: - Passion for clean, reliable, and scalable data. - Strong problem-solving skills with debugging mindset. - Balance of software engineering rigor and data intuition. - Collaborative communicator who thrives in cross-functional environments. Required Experience & Skills (Minimum): - 3+ years in data engineering or back-end development. - Strong Python and SQL skills. - Experience with at least one major data warehouse (Snowflake, Redshift, BigQuery). - Familiarity with pipeline orchestration tools (Airflow, Prefect). Ideal Experience & Skills: - Experience with dbt for transformations and data modeling. - Streaming data experience (Kafka, Kinesis, Pub/Sub). - Cloud-native data platforms (AWS Glue, GCP Dataflow, Azure Data Factory). - Background in regulated industries (healthcare, finance) with strict compliance. What Does a Typical Day Look Like? A Data Engineer’s day revolves around keeping pipelines running, improving reliability, and enabling teams with high-quality data. You will: - Check pipeline health in Airflow/Prefect and resolve any failed jobs. - Ingest new data sources, writing connectors for APIs or SaaS platforms. - Optimize SQL queries and warehouse performance to reduce costs and latency. - Collaborate with analysts/data scientists to deliver clean datasets for dashboards and models. - Implement validation checks to prevent downstream reporting issues. - Document and monitor pipelines so they’re reproducible, scalable, and audit-ready. In essence: you ensure the business has accurate, timely, and trustworthy data powering every decision. Key Metrics for Success (KPIs): - Pipeline uptime ≥ 99%. - Data freshness within agreed SLAs (hourly, daily, weekly). - Zero critical data quality errors reaching BI/analytics. - Cost-optimized queries and warehouse performance. - Positive feedback from data consumers (analysts, scientists, leadership). Interview Process: - Initial Phone Screen - Video Interview with Pavago Recruiter - Technical Task (e.g., build a small ETL pipeline or optimize a SQL query) - Client Interview with Engineering/Data Team - Offer & Background Verification

• Design and implement robust data architectures supporting structured and unstructured data from internal and external sources • Build and maintain scalable, secure data pipelines using cloud-based and distributed technologies • Establish data structures and routing mechanisms based on business and technical requirements • Develop and execute automated test cases to validate ETL workflows, data pipelines, and reporting logic • Create regression test suites to ensure ongoing data integrity and system stability • Analyze current and historical performance data to identify trends, variances, and opportunities • Collaborate with data consumers, project managers, and business stakeholders to define logical and physical database designs for analytics models • Identify and implement improvements in internal data management and testing processes

• Work directly on storage infrastructure, product launches, and new customer experiences built on one of the most advanced AI systems in the world • Collaborate daily with researchers and engineers who are some of the best in the world at what they do • Run implementations end-to-end and see initiatives through to real outcomes — no waiting around to be told what to do • Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy

Role Description Amplify is seeking a SIOP Data & Model Specialist to join our Central Services Technology team. This role owns the technology backbone and planning science of Supply Chain Sales, Inventory, and Operations Planning (SIOP), building and governing the framework that underpins forecasting, demand/supply planning, and scenario modeling. You'll serve as a bridge between supply chain expertise and technical implementation, owning planners' Excel templates and the structured planning technology layer (currently dbt-based) while leading the transition from spreadsheets to a policy-driven planning process. The ideal candidate brings deep expertise in forecasting, inventory modeling, demand/supply planning, and operational workflows, with the ability to translate supply chain subject matter knowledge into scalable planning solutions. You'll drive forecasting accuracy and scenario modeling while partnering closely with planners to gain a deeper understanding of day-to-day operations. Success is measured by operational metrics, including fill rate, forecast value add (FVA), inventory turns, and expedite costs, as you collaborate with Data/Technology teams on architecture and Finance on policy guardrails to enable long-term supply chain resilience. Essential Responsibilities - Governance & Decision Rights: - Approve/deny changes to planning templates and dbt models. - Set and govern policy parameters (service levels, safety stock, MOQ/EOQ, freeze fences). - Gate planning releases and prioritize SIOP backlog. - Call stop-the-line on non-compliant processes. - Model Development: - Lead migration from Excel to governed dbt frameworks in Snowflake. - Collaborate with analytics engineers to build forecast models (time-series, causal), inventory policies (multi-echelon), and FVA diagnostics. - Develop demand sensing approaches of market data to improve FVA. - Maintain semantic layer with version control and clear documentation. - Data Integration & Quality: - Own integrations with NetSuite and Salesforce. - Partner with data engineering on ETL processes. - Establish data quality rules. - Monitor data health proactively and enforce quality standards and validation processes. - Scenario Planning & Analytics: - Build and manage dbt sandbox for "what-if" analysis. - Run scenario planning for build-to-stock and adoptions. - Develop simulation capabilities for supply chain configurations and demand fluctuations. - Create dashboards for planning visibility. - Collaboration & Training: - Train planners and establish certification for template/dbt usage. - Mentor colleagues on modeling and technology best practices. - Partner with Finance on working-capital targets. - Generate and review Pull Requests for production integration. - Process Standardization: - Standardize master data needed for SIOP with Product Data Integrity. - Publish playbooks for call-downs and expedites. - Track adoption and compliance. - Ensure roadmap alignment with business objectives. Qualifications - Bachelor’s degree in Industrial Engineering, Operations Research, Applied Statistics or other engineering- or analytics-based discipline (MS preferred). - 6–10+ years experience in planning science (forecasting, inventory optimization) with hands-on modeling. - Strong SQL and dbt experience; advanced Excel skill set, and at minimum a familiarity with Atlan / Snowflake or an equivalent platform. - Proven product ownership of analytics/plan platforms including management of the backlog, releases, and change control. - Demonstrated change leadership with planners with measurable FVA and adoption wins. - Experience working in a cross-functional or centralized technology/process improvement team. Preferred Qualifications - Experience with ERP and CRM (preferably, NetSuite and Salesforce) integration. - An understanding of K-12 education business model and seasonality. - Experience in dealing with complex independent and dependent demand scenarios driven by complex kits and BOMs. - Excellent communication skills with the ability to convey complex data models to non-technical stakeholders. - Familiarity with continuous improvement methodologies (e.g., Lean, Six Sigma), quality assurance practices, or structured project/change management frameworks. Benefits - Salary is only one component of the Amplify Total Rewards package, which includes a 401(k) plan, competitive health insurance and mental health options, basic life insurance, paid time off, parental leave, and access to best-in-class development programs. - The gross salary range for this role is $120,000 - $140,000. - This role is eligible to earn an annual discretionary bonus that rewards individual and company performance. Company Description Amplify is an Equal Opportunity Employer. Amplify makes employment decisions based on qualifications and merit, and does not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, veteran status, or any other legally protected characteristic or status. Amplify is committed to providing reasonable accommodations for qualified individuals with disabilities, including disabled veterans. If you have a disability and need an accommodation in connection with the application or hiring process, please email hiringaccommodations@amplify.com. If you are selected for employment, a background check will be required. As required by state and local laws and district policies, you may be required to provide additional documentation, such as proof of vaccination, or submit to enhanced background screening, such as fingerprinting. Amplify is an E-Verify participant.