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.

Role Description We’re looking to add a dynamic DataOps Engineer, reporting to our Manager of Data Operations. As a DataOps Engineer, you will focus on the implementation, monitoring, and basic maintenance of our SQL databases. You will use IAC to assist with deployments of our database components. You will support engineering teams in implementing database design best practices across a variety of applications. We are building out a DataOps Team to design and implement our next generation data architecture including AWS, Aurora MySQL, Aurora PostgreSQL, and Snowflake. Responsibilities: - Assist senior engineers in the design of data models and schemas, and participate in code walk-throughs. - Support performance tuning efforts on SQL queries regarding applications, storage, and network. - Explore and utilize AI-powered tools and automation solutions to increase efficiency in DataOps workflows and reduce manual toil. - Follow established processes for data quality, data governance, testing, and on-going monitoring. - Assist in the analysis of current systems and support the implementation of database designs to support our business applications. - Adhere to established data models, modeling naming standards, abbreviations, guidelines, and best practices. - Assist in translating logical data models and implementing physical database structures. - Monitor data service costs and flag potential cost inefficiencies to senior team members. - Maintain and update documentation for database architectures. Qualifications - At least 3 years of cloud database design & implementation experience including: - Proficiency with SQL database solutions including Aurora PostgreSQL, Aurora MySQL, and Snowflake. - Proficiency with SQL and writing performant queries; we use MySQL, PostgreSQL, and SnowSQL. - Proficiency with database IAC frameworks; we use Terraform/OpenTofu. - Strong experience with relational database design and data modeling techniques. - Familiarity with leveraging AI-powered tools and scripting for automation in areas like monitoring, alerting, or system maintenance. - Experience with data security and data governance techniques. - Experience monitoring database systems and independently researching and resolving incidents; we use AWS services such as RDS Database Insights and CloudWatch as well as Datadog. - AWS Certification preferred. - Highly collaborative team player. - Strong programming experience, preferably in Python, or other object-oriented language. - Build highly reliable systems. - Strong diagnostic skills. - Strong organizational and communication skills. Requirements The annual base salary range for this role represents PayNearMe's good-faith estimate of the base salary it reasonably expects to offer for this position at the time of hire. Actual compensation may vary based on factors including the candidate's experience, qualifications, skills, and work location. PayNearMe may offer compensation outside of this range in certain circumstances. This position will remain posted until filled. Annual Salary Range: $1 - $10 USD Benefits - Competitive salary and benefits with growth-company options grant. - Fast-paced and professional work culture. - Stock options with standard startup vesting - 1 year cliff; 4 years total. - $50 monthly communication expense stipend to go towards your phone/internet bill. - $250 stipend to enhance your WFH setup. - Reimbursement for peripheral equipment: monitor (up to $400), keyboard and mouse (up to $200). - Premium medical benefits including vision and dental (100% coverage for employees). - Company-sponsored life and disability insurance. - Paid parental bonding leave. - Paid sick leave, jury duty, bereavement. - 401k plan. - Flexible Time Off (our team members typically take off ~3-4 weeks per year). - Volunteer Time Off. - 13 scheduled holidays.

Role Description Our client is looking for a Data Engineer to join our team and bring the analytics practice to the next level. They are looking for a motivated person who thrives in a dynamic and challenging environment, who loves working with tools on the edge, who has no problem switching between multiple programming languages, and who is able to find out-of-the-box solutions to solve complex problems. In this role, you will be at the heart of the definition and implementation of world-class analytics solutions, and you will contribute to set data as a strategic advantage for the manufacturing client. Responsibilities - Design, develop, implement and support robust ETL/ELT/Data Pipelining solutions - Coordinate with multiple development teams to achieve delivery objectives - Provide support in requirements definition, estimation, development and delivery of robust and scalable solutions - Development and support of real-time data ingestion processes from various data sources - Development and support of data models optimized for business intelligence usage - Build integrations with APIs from external providers such as Google, Facebook, Salesforce, SAP and others - Adhering to industry standards and laws such as GDPR and SOX - Be a leader in best-practices definition and creative thinking Qualifications - Master Degree in Computer Science, Business Intelligence or equivalent - Solid and demonstrated experience on following technologies: - Snowflake - DBT - Microsoft SQL Server - Power BI - Git - Fluent in various programming languages such as: - SQL - Python - Understands and puts into practice data modeling, design and development of solid ETL/ELT data pipelines - Fluent in writing, executing and optimizing complex SQL queries - Experience implementing API Service architectures (REST) - Develop clean and maintainable code in a CI-CD Environment - Experience in using cloud BI technologies such as Azure or similar - Experience in translating business requirements into advanced data models able to fulfill analysts and data scientists requirements - Experience in data profiling - Experience in working within an agile team to build big data / analytics solutions - Strong interpersonal relations, motivated and loves to work on multiple challenging projects - Strong communication skills, both speaking or writing - Fluent in English. French or Portuguese is a great asset - Open-minded and able to adapt to new ways of working (data vault, event-driven architecture, unstructured data, self-service analytics, etc.) - Well organized and able to self-prioritize, sometimes with conflictual deadlines - Continuously seeks for improvements and craves to put hands on new technologies

Role Description We are looking for a curious, driven, and innovative Senior Data Engineer who proactively takes initiative to solve complex problems and lead the development of data assets that elevate our marketing analytics capabilities. - Architect & Scale Data Pipelines: - Design, build, and maintain robust, scalable ingestion pipelines from a diverse suite of marketing sources (APIs, SFTPs, webhooks etc.), ensuring high availability and data integrity. - Optimize Core Data Assets: - Develop, maintain, and tune high-performance dbt models to transform raw marketing data into production-ready analytic assets for cross-functional reporting. - Drive Infrastructure Efficiency: - Audit and refactor existing data infrastructure to uncover cost efficiencies and optimize compute performance across marketing data sets. - Accelerate AI Readiness: - Develop and scale semantic layers and data models specifically tailored to fuel downstream AI use cases and predictive marketing analytics. - Champion Governance & Literacy: - Author comprehensive data documentation, lineage maps, and artifacts to elevate data literacy and foster a culture of self-service across the organization. - Lead Cross-Functional Partnerships: - Act as the primary engineering partner to the Marketing Analytics team, translating complex business requirements into high-impact, performant data products. - Bridge IT & Engineering: - Collaborate closely with IT and core Data Engineering teams to align architectural standards, bridge capability gaps, and foster a cohesive, modern data ecosystem. - Serve as a Subject Matter Expert: - Act as a key technical resource for data engineering best practices, scalable architectural design, and marketing data usage. - Drive Technical Excellence & Mentorship: - Act as a technical mentor to elevate the team's engineering capabilities, driving continuous skill development and championing modern best practices across analytics and engineering cohorts. Qualifications - B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). - Proven ability to write clean, modular, testable, and maintainable code. - Strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. - Hands-on experience managing and processing large-scale digital marketing datasets efficiently across cloud infrastructure. - Experience implementing Medallion architecture and a solid understanding of data warehouse design and schema structuring. - Expert-level knowledge of dbt (Core) for modular data modeling. - Proficient with Git workflows and integrating pipelines into automated CI/CD deployment workflows. Requirements - Intellectual curiosity and a desire to deepen knowledge and continue learning. - Take responsibility to proactively advance projects and contribute to the organization. - Initiative to understand the full scope of business problems and propose solutions. - Ability to explain technical concepts clearly to technical and non-technical audiences. - Work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Benefits - Ski/Mountain Perks: Free passes for employees, employee discounted lift tickets for friends and family, and free ski lessons. - Employee discounts on lodging, food, gear, and mountain shuttles. - 401(k) Retirement Plan. - Employee Assistance Program. - Excellent training and professional development. - Health Insurance; Medical, Dental, and Vision Insurance plans (for eligible seasonal employees after working 500 hours). - Free ski passes for dependents. - Critical Illness and Accident plans. - Remote work options from various U.S. states and British Columbia.