Role Description As a GCP Data Engineer at Zensar, you will be responsible for: - Designing and implementing data processing systems on Google Cloud Platform (GCP). - Collaborating with data scientists and analysts to optimize data pipelines. - Ensuring data quality and integrity throughout the data lifecycle. - Building and maintaining scalable data architectures. - Monitoring and troubleshooting data processing workflows. Qualifications - Bachelor's degree in Computer Science, Engineering, or a related field. - Experience with GCP services such as BigQuery, Dataflow, and Pub/Sub. - Proficiency in programming languages such as Python or Java. - Strong understanding of data modeling and ETL processes. - Familiarity with data warehousing concepts. Requirements - 3+ years of experience in data engineering or a related field. - Experience with SQL and NoSQL databases. - Ability to work in a fast-paced environment and manage multiple priorities. - Excellent problem-solving and analytical skills. - Strong communication and collaboration skills. Benefits - Competitive salary and performance-based bonuses. - Comprehensive health and wellness benefits. - Opportunities for professional development and career growth. - Flexible work arrangements and work-life balance. - Inclusive and diverse workplace culture.

• Design, develop, and maintain databases supporting IVR and contact center systems • Support databases used by runtime IVR services and analytics platforms • Design and maintain relational data models for IVR event, routing, and call data • Write, maintain, and optimize SQL for application logic, configuration changes, and investigations • Ensure database availability, integrity, performance, and scalability in production environments • Support storage and availability of IVR event logs, call lifecycle data, and routing outcomes for analytics and reporting • Monitor and troubleshoot production databases and support incident investigations • Collaborate with architects, application developers, DevOps, QA, and Analytics teams on platform changes and improvements

Role Description Our Customer Data Engineers own data integration with our customers, ensuring they get value from Gridsight's platform quickly and seamlessly. This is equal parts customer-facing and technical. You'll work directly with utility customers to help them understand what data we need, review what they send, give feedback on issues, and get it into the platform. You'll spend roughly half your time in conversations with customers and half heads-down wrangling data, running transforms, and configuring the system. What makes this role distinctive is where it's heading. We're continuously building better tooling to streamline data onboarding, and we want someone who accelerates that shift. From day one, we expect you to approach the work with a tool-first mindset — questioning manual steps, reaching for automation, and helping us develop internal products that make it a faster, more repeatable process. Over time, the role can grow in two directions: deeper into product engineering, or deeper into customer ownership and leadership. We'll support whichever direction plays to your strengths. Qualifications - Strong communication skills — you can explain technical data requirements to non-technical people, give constructive feedback, and manage expectations with confidence. - Proactive and self-directed — you see what needs doing and drive it to completion without close supervision. - Strong SQL skills with demonstrated ability to analyse, validate, and wrangle messy datasets. - Experience with dbt or similar ELT frameworks, and exposure to working within data pipelines. - Experience in customer-facing or consulting-style technical roles with external stakeholder management. - Comfort with ambiguity — customer data environments are inconsistent and varied, and there won't always be a playbook. - Ability to manage your own time and priorities across multiple concurrent customer engagements. - 3+ years of professional experience in data engineering, data analysis, technical consulting, or a similar role involving both technical and stakeholder-facing work. Requirements - Work directly with utility customers to help them understand what data Gridsight requires, in what format, and how to provide it. - Review incoming customer data against expected schemas and quality standards, providing clear and constructive feedback on issues. - Onboard customer data into the platform using tooling and transformation workflows. - Identify and act on opportunities to improve our internal tooling, automating manual steps, improving validation, and making the data onboarding process more efficient, high quality and repeatable. - Drive customer data deliveries to completion — following up, unblocking, and maintaining momentum through the implementation process. - Manage complex customer situations with composure: unrealistic timelines, incomplete data, shifting priorities, and competing demands. - Identify and act on opportunities to automate manual steps, improve tooling, and make the data onboarding process more efficient and repeatable. What Would Set You Apart - A track record of improving processes — automating manual work, building internal tools, or introducing better ways of working. - Expertise in leveraging AI-assisted development tooling. - Experience in energy, utilities, or infrastructure domains. - Experience with data quality frameworks, monitoring, or observability. Benefits - Competitive salary and equity package. - Remote-first, with head office in Sydney. - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter. - A role with clear growth pathways into product and tooling, or deeper customer ownership.

Role Description As the WASH Data Fellow, you will contribute to World Vision’s mission, advancing access to clean water, sanitation, and hygiene as foundations of child well-being. This role supports World Vision’s five-year Global WASH Business Plan spanning 42 countries and emphasizing innovation, advanced analytics, and data-informed decision-making. - Keep Christ central in individual and corporate life. - Query and manipulate programmatic output and financial data through ETL processes from multiple databases to prepare multi-dimensional datasets for ongoing analysis and dynamic forecasting. - Lead Machine Learning and Data-Informed Solutions: Design and implement data engineering and analytics pilot projects to enhance WASH programs’ long-term impact and sustainability. - Build Data Accessibility: Create near-real-time data visualization products for WASH team members. - Analyze Data from Remote Sensing & Hydraulic Models: Collaborate with team members to analyze data from small scale rural water system meters. - Communicate Project Results: Contribute to creating reports, visualizations, and presentations that showcase the impact of our WASH work. - Engage in Mentorship and Professional Development: Work with and be mentored by WASH leaders. Qualifications - Bachelor's degree is required. - Ability to clean, join, and analyze structured datasets to answer programmatic or financial questions. - Ability to implement or adapt basic predictive or classification models using existing libraries, with guidance. - Ability to build data pipelines between systems using APIs, scripts, or other methods as necessary. - Interest in learning about and working in the WASH sector. Requirements - Bachelor's degree is required. - Ability to clean, join, and analyze structured datasets to answer programmatic or financial questions. - Ability to implement or adapt basic predictive or classification models using existing libraries, with guidance. - Ability to build data pipelines between systems using APIs, scripts, or other methods as necessary. - Interest in learning about and working in the WASH sector. Benefits - Estimated hiring range is $27 - $33.50 per hour. - The posted hiring salary range reflects pay for U.S. locations and is determined using market data and internal compensation guidelines. - Actual compensation may vary depending on the candidate’s geographic location, job-related experience, and applicable laws.