Role Description We at Coforge are hiring a Senior Data Engineer with the following skill set. Key Responsibilities - Delivery & Ownership - Own the end-to-end delivery of data pipelines and data products, from design through deployment and production support. - Develop, maintain, and optimise scalable data pipelines using Azure Databricks, DBT, and Python. - Ensure solutions are production-ready, reliable, and meet defined SLAs. - Migration & Platform Engineering - Execute and support migration of data from Snowflake (AWS) to Azure using Databricks, DBT, and Lakebridge. - Build and manage infrastructure-as-code using Terraform to enable scalable and repeatable deployments. - Ensure seamless integration between legacy systems and the Azure data platform. - Data Quality, Observability & Governance - Implement data quality frameworks (e.g., DBT testing, validation rules) to ensure trusted data pipelines. - Enable observability through logging, monitoring, and alerting of pipelines and data workflows. - Support data governance standards including data lineage, consistency, and compliance requirements. - Architecture & Engineering Excellence - Contribute to the design and architecture of scalable data solutions, aligned with lakehouse principles. - Apply best practices in data modelling, performance optimisation, and cost efficiency. - Follow and promote engineering standards, including modular design and reusable components. - Production Support & Reliability - Monitor and maintain data pipelines in production, ensuring high availability and performance. - Troubleshoot issues and perform root cause analysis (RCA) for incidents. - Continuously improve system stability, resilience, and operational processes. - Collaboration & Technical Leadership - Work closely with cross-functional teams (data, product, architecture, business) to translate requirements into scalable technical solutions. - Provide guidance and mentorship to junior engineers through code reviews and best practices. - Contribute to documentation of architecture, pipelines, and operational processes. Qualifications - Strong hands-on expertise with: Azure Databricks, DBT, Snowflake, Python and SQL. - Proven experience building and managing large-scale data pipelines and transformations. - Experience working with high-volume datasets (e.g., terabytes, complex data models, multiple pipelines). - Solid understanding of: Data modelling and ETL/ELT frameworks, Distributed data systems and lakehouse architectures, Experience with Terraform and infrastructure-as-code principles. - Strong experience with CI/CD pipelines and Git-based version control. - Experience supporting production systems, including monitoring, alerting, and incident resolution. - Knowledge of data quality, testing, and observability frameworks. - Strong problem-solving and analytical skills. - Excellent communication skills with the ability to work across technical and non-technical stakeholders. - Experience in insurance or financial services domains is highly desirable. Preferred Skills - Experience with real-time/streaming technologies (Kafka, Event Hubs, Delta Live Tables). - Knowledge of security, compliance, and data protection standards in regulated industries. - Experience with cost optimisation and performance tuning in cloud environments. - Exposure to multi-cloud or hybrid architectures. Posted On 14-07-2026 At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

• Develop, design, and maintain Power BI dashboards, reports, and data visualizations based on business requirements. • Build efficient data models (star schema, semantic models) using Power BI and Microsoft Fabric components. • Work with Microsoft Fabric features such as Lakehouse, Data Engineering pipelines, Dataflows Gen2, and Warehouse where applicable. • Optimize datasets, visuals, DAX queries, and report performance. • Collaborate with business stakeholders and technical teams to gather requirements and translate them into scalable reporting solutions. • Ensure data accuracy, governance, and compliance with organizational standards. • Troubleshoot issues related to datasets, refresh failures, permissions, and report performance. • Support the modernization of analytics platforms and the adoption of Microsoft Fabric within the KPMG ecosystem.

Role Description Function Health is building the most comprehensive picture of human health ever assembled and making sense of that data is core to our mission. We're looking for a Staff Analytics Engineer to own the semantic layer that sits at the heart of our data platform: the trusted, well-modeled foundation that powers dashboards, self-serve analytics, and increasingly, AI-driven data agents. This isn't a greenfield "figure out what to build" role. We have a platform. Now we need someone to make it exceptional, clean models, a well-governed metrics layer, and the architecture to let AI query our data reliably and accurately. You'll collaborate closely with data scientists, product engineers, and business leaders to ensure that when anyone (or anything) asks a question about our data, they get the right answer. This is a fully remote role. Function Health is a distributed team, we hire across the US. Key Responsibilities - Own the semantic layer: Design and maintain the metrics, dimensions, and data models that serve as the single source of truth across the business — built to be queried by humans and AI alike. - Architect for AI-readiness: Structure our Databricks and GCP-based data platform so it can reliably power AI-driven analytics agents — clean schemas in Unity Catalog, consistent naming conventions, and strong data contracts. - Drive data quality end-to-end: Build observability, testing, and alerting into pipelines so we catch problems before stakeholders do. - Enable self-serve analytics: Partner with product, clinical, and business teams to deliver tooling and dashboards that let them answer their own questions without filing tickets. - Set the standard: Establish and enforce data modeling conventions, documentation practices, and code review norms across the data org. - Collaborate cross-functionally: Translate ambiguous business questions into data solutions; work with product engineering to improve event logging and measurement coverage. Qualifications - 8+ years of analytics engineering or data engineering experience, with clear progression to staff-level scope and impact. - Deep SQL expertise and strong Python skills. - Strong data modeling fundamentals — you know what clean, extensible, well-documented models look like and can build and enforce that standard regardless of tooling. Experience with dbt is a plus. - Experience with modern data stack tools: Databricks, Snowflake or BigQuery, Airflow or similar orchestration, Looker/Tableau or equivalent BI tools. - Track record of building resilient, monitored, production-grade data systems — not just pipelines that work, but ones that stay working. - Strong communicator who can make technical tradeoffs legible to non-technical stakeholders. Requirements - Bias Toward Action: Demonstrated ability to take initiative, make decisions under uncertainty, and move projects forward even in the face of ambiguity. - Entrepreneurial Spirit: Strong adaptability to changing business needs with a knack for building and optimizing processes. - Communication: Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders. - Remote Work Adaptability: Comfort with remote work environments, demonstrating the ability to stay productive and connected with the team irrespective of physical location. - Continuous Improvement: A willingness to question assumptions and a commitment to continuous improvement. Nice-to-Have Skills and Experiences - Experience with health tech or regulated data environments (HIPAA, PHI/PII handling). - Familiarity with Databricks Unity Catalog, Delta Lake, or Spark. - Experience building or integrating with AI/LLM-powered analytics tools or data agents. - GCP experience. Core Values - Ruthless Prioritization: We don’t let perfect get in the way of progress. - Member-First, Always: We design and deliver like we’re caring for someone we love. - One Team, Moving Fast: We are aligned in purpose, prioritization, and speed. - Radical Ownership, Relentless Execution: We don’t just ship– we own outcomes and drive results. - Mission Over Ego: We are ruthlessly aligned to our mission– and leave ego at the door. - Sustained Integrity in Every Detail: We earn trust by obsessing over accuracy, quality, and clarity in everything we do. Benefits - Competitive salary and benefits package. - Flexible working hours. - Dynamic work environment where creativity and innovation are encouraged. Important Notice Legitimate communication from the Function Health team will always come from an email address ending in @functionhealth.com. Function Health will never request personal information such as banking details or payment during the hiring process. Please be cautious of communications or job offers that come from other email domains, instant messaging platforms, or unsolicited calls. If you ever have doubts about the legitimacy of a communication, please reach out to us directly at talent@functionhealth.com.

Role Description We at Coforge are hiring a Lead Data Engineer with the following skill set. - Lead and mentor a team of data engineers, setting technical direction, conducting code reviews, and promoting engineering excellence. - Own the end-to-end architecture and design of the data platform, ensuring scalability, reliability, and alignment with business needs. - Take full ownership of implementation delivery, from design through deployment, ensuring high-quality, production-ready solutions. - Define and drive the data migration strategy from Snowflake / SSIS to Azure Databricks and DBT, including architecture decisions and execution oversight. - Collaborate closely with cross-functional stakeholders (data, product, architecture, and business teams) to translate requirements into robust technical designs. - Design and oversee the development of scalable data pipelines and data models, ensuring best practices in performance and maintainability. - Lead the implementation of infrastructure-as-code using Terraform, enforcing consistency and automation across environments. - Establish and enforce architectural standards, design patterns, and engineering best practices across the data ecosystem. - Ensure reliable and efficient data integration between Legacy system and Azure environments, with strong focus on data quality and observability. - Drive CI/CD adoption and oversee release processes for data pipelines and platform components. - Act as the primary technical owner for troubleshooting complex issues and ensuring long-term stability of the platform. - Maintain comprehensive documentation of architecture, design decisions, and implementation standards. Qualifications - Proven experience owning system design and leading implementations of large-scale data platforms. - Strong hands-on expertise with Snowflake, Azure Databricks, and DBT with strong Python. - Will have worked on large scale data transformations comprising of thousands of DBT models and data pipelines handling terabytes of data daily. - Deep understanding of data architecture, data modelling, and distributed data systems. - Extensive experience with Terraform and infrastructure-as-code principles. - Demonstrated experience leading cloud-to-cloud data migration projects (AWS to Azure preferred). - Strong experience with CI/CD pipelines and Git-based version control. - Advanced SQL skills and deep knowledge of ETL/ELT frameworks. - Strong problem-solving skills with the ability to make architectural trade-offs and decisions. - Excellent communication skills, with the ability to influence both technical and non-technical stakeholders. - Ability to thrive in a fast-paced, ownership-driven environment. - Previous experience in the insurance or financial sector industry, with strong understanding of core domains such as claims, policies, underwriting, and risk. - Will have managed teams with a level of maturity and able to demonstrate key success outcomes with these teams. - Will have managed low, mid and top performers within the team to get the best from them via mentoring, development and training needs where needed. Preferred Skills - Experience implementing data governance, observability, and quality frameworks. - Strong knowledge of security and compliance standards in insurance or financial services. - Experience with real-time and streaming data technologies (Kafka, Event Hubs, Delta Live Tables). - Familiarity with lakehouse architecture and cost/performance optimization strategies. - Experience operating in multi-cloud or hybrid cloud environments. Company Description At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.