• Use of Claude Code to accelerate engineering, orchestration of agentic workflows, and integration via MCP • Develop and optimize scalable, reliable, and efficient data pipelines • Implement processes and tools to ensure data quality, accuracy, and consistency, as well as documentation throughout the data lifecycle • Work with large volumes of heterogeneous data, transforming them into insights to support decision-making • Identify opportunities to optimize workflows and recommend improvements to the existing data infrastructure • Build and maintain analytical models (Gold layer) that support dashboards, reports, and data products for business teams

• Build and manage reliable data pipelines encompassing ingestion/collection, processing, integration, storage, and making data available across the organization. • Work within a distributed systems architecture for massively parallel (MPP) data processing, combining diverse heterogeneous data sources and collaborating with analytics and data science teams to develop solutions and deliver data-driven value.

Role Description Looking for Philippines-based candidates. Job Role: Lead Data Engineer Compensation range: $4,000-5,000 AUD / Monthly (depending on experience and client discretion) Engagement type: Independent Contractor Agreement Work Schedule: This role is expected to align with the AU business hours (approx. 9 AM - 5 PM, Monday to Friday) for collaboration, but as a contractor, you’ll have flexibility in how you manage your time. Role Overview: This role is central to the successful design, build, and ongoing governance of a DataHub. The Lead Data Engineer acts as the primary interface between offshore and onshore teams, setting architectural direction and engineering standards while ensuring consistent code quality and adherence to agreed design principles. During the build phase, the role oversees architecture decisions, coordinates with IT teams on core data layer delivery, and approves work prior to UAT release. As delivery transitions from build to run, the role shifts into operational ownership—managing DataHub SLAs, overseeing new dataset intake, and serving as the escalation point for production issues. The role also requires strong stakeholder engagement, including facilitating agile ceremonies and communicating effectively with both technical and non-technical audiences across a distributed, cross-timezone team. Key Responsibilities - Own the dbt project architecture, including model structure, naming conventions, testing standards, CI/CD pipelines, and documentation frameworks to ensure consistency across all engineering work. - Manage the dataset delivery backlog with onshore stakeholders, including phase scoping, validation of source data availability, and sequencing of builds to maximise business value. - Govern code quality by reviewing all Silver and Gold models prior to UAT, ensuring no production deployment occurs without lead approval. - Own the end-to-end dataset handover process from Build to Run, including test sign-off, data catalogue documentation, observability configuration, and operational runbooks. - Coordinate and prioritise work across Build and Run workstreams operating in parallel, ensuring alignment and delivery efficiency. - Participate in standups (async where required) and lead sprint demonstrations on a fortnightly basis. - In Run steady state operations, own DataHub SLA performance, oversee new dataset onboarding, and act as the final escalation point for production support issues. Run & Steady-State Responsibilities - Own DataHub SLA performance, ensuring pipeline uptime and data freshness commitments are met across all production Gold datasets. - Manage new dataset intake from onshore teams, scoping requests and determining whether they require a new build phase or can be absorbed into the Run team. - Act as the primary escalation point for onshore stakeholders and the final offshore escalation for critical incidents that cannot be resolved by the data operations team. Qualifications - 7+ years data engineering experience (including 2+ years in a team lead or principal engineer role) - Snowflake (advanced): warehouse management, RBAC, dynamic data masking, Snowflake Tasks, performance tuning, and query optimisation - dbt Cloud (advanced): incremental models, snapshots, macros, packages, Semantic Layer / MetricFlow, CI/CD using GitHub Actions - Python (intermediate): Snowpark, pipeline scripting, and data quality automation - Data modelling (expert): dimensional modelling, medallion architecture (Bronze / Silver / Gold), and retail data models (orders, inventory, customers) - Git (advanced): branching strategies, PR workflows, and managing shared dbt projects across multiple engineers - Azure Data Factory (intermediate): pipeline monitoring and troubleshooting; ability to engage IT credibly on pipeline issues (build owned by IT) - Retail domain knowledge (preferred): familiarity with order management, inventory planning, and DTC data structures - AI & Automation Tools: Hands-on experience with tools such as GitHub Copilot, Cursor, Claude (or similar LLMs), Snowflake Cortex AI_COMPLETE, Elementary, and data observability platforms for AI-assisted development, SQL debugging, anomaly detection, alert classification, incident reporting, and workflow automation. What Success Looks Like - Excited to build and scale a modern data platform from the ground up - Proven experience leading data engineering teams and maintaining engineering quality standards - Comfortable working with separate upstream data delivery teams - Has built dbt medallion architecture projects (Bronze / Silver / Gold) from scratch - Strong quality ownership; confident holding back datasets not ready for UAT - Uses AI tooling naturally as part of day-to-day engineering workflows - Owns AI triage pipeline accuracy and incident log quality - Ensures alerts are acknowledged and resolved within agreed SLAs - Maintains accurate documentation and quality certifications across Gold datasets - Experienced in operating and tuning data pipeline monitoring and alerting processes - Able to communicate incidents clearly to business stakeholders in concise, non-technical language - Thrives in stable, operational environments where reliability is critical - Understands escalation boundaries and collaborates effectively with senior engineers Work Arrangement & Expectations This is a remote role that will be set up as an independent contractor engagement. To ensure alignment and transparency, successful candidates will be expected to: - Disclose any existing ongoing roles or client work - Reflect this engagement on their LinkedIn profile (clearly marked as “Independent Contractor”)

Role Description Inviting applications for the role of Principal Consultant Azure Data Engineer with Gen AI Skills. In this role you will design, build, and maintain scalable data pipelines and platforms that power business intelligence, advanced analytics, and AI-driven solutions. You will work closely with data scientists, analysts, and business stakeholders to deliver high-quality, reliable data products. - Design, develop, and maintain robust ETL/ELT data pipelines on Azure cloud infrastructure (Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics). - Build and optimize large-scale data processing workflows using Azure Databricks and Apache Spark. - Collaborate with AI/ML teams to engineer data pipelines and feature stores that support Generative AI and machine learning models. - Leverage Microsoft Copilot and AI-assisted tools to accelerate development, automate repetitive tasks, and improve code quality. - Write, optimize, and maintain complex SQL queries, stored procedures, and data models for analytical workloads. - Ensure data quality, lineage, governance, and security across all data assets. - Develop and maintain data documentation, metadata management, and data cataloging practices. - Participate in code reviews, architecture discussions, and agile ceremonies. - Support and enhance BI/visualization dashboards using Tableau or equivalent tools (Power BI, Looker, etc.) for actionable business insights. Qualifications - Bachelors - Business Analytics - Bachelors - Computer Science - Bachelors - Statistics - Masters - Data Science - Certified Data Management Professional - Riversand - Databricks Certified Associate Developer for Apache Spark 3.0 - Databricks Academy - Databricks Certified Associate Developer for Apache Spark - Databricks Academy - Microsoft Certified: Azure Data Engineer Associate - Microsoft - Oracle Database 12c Certified Implementation Specialist - Oracle Requirements - Agile Methodology - Banking Capital Markets - Client Relations - Cloud Computing - Collaboration Tools - Commercial Sales - Consumer Packaged Goods (CPG) - Databricks Platform - Data Engineering - Data Literacy - Design Thinking - Electronic Hardware - Executive Presence - Inclusion - Manufacturing Equipment - People Leadership - Personal Effectiveness - Risk Management - Semiconductors - Snowflake (Platform) - Sourcing and Procurement - Storytelling Benefits - Lead AI-powered transformation – Drive innovation and solve real-world business challenges that matter. - Make an impact – Help global enterprises solve business challenges that matter. - Accelerate your career – Gain hands-on experience, mentorship, and world-class learning opportunities to stay ahead. - Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day. - Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress.