Data Engineer

This is a remote position. About KIS KIS is a global technology consultancy, 100% remote and headquartered in the United States. We partner with companies ranging from innovative startups to large multinational organizations, helping them build modern, scalable, and high-impact technology solutions. Our global team works on challenging projects across different industries, combining technical excellence, innovation, and close collaboration with our clients. We are currently looking for aMid-Level Data Engineerto join our team and work on a challenging project for one of KIS's leading international clients. What You'll Do As a Mid-Level Data Engineer, you will be responsible for designing, building, and maintaining reliable and scalable data solutions. You will work closely with engineers, analysts, and stakeholders to ensure high-quality, accessible, and well-structured data across the organization. Your responsibilities will include: - Design, build, and maintain end-to-end data pipelines, including batch and/or streaming workflows, from ingestion through transformation and delivery. - Develop and operate reliable, scalable, and high-performing ETL/ELT workflows. - Write efficient, production-grade SQL queries for data extraction, transformation, and analytics use cases. - Implement and maintain data models, including star schemas and incremental models, optimized for analytics and reporting. - Develop reusable, modular, and maintainable Python code for data transformations and pipeline logic. - Monitor data pipelines, troubleshoot failures, and perform root cause analysis across code, orchestration tools, data sources, and cloud services. - Ensure data quality by implementing automated validation checks, including schema validation, freshness checks, and row-level assertions. - Build AI Agents to streamline data platforms, engineering processes and reporting. - Collaborate with analysts, backend engineers, and other stakeholders to define data contracts and ensure reliable data availability. - Actively participate in planning, estimation, and prioritization of data engineering tasks. - Proactively identify risks related to performance, scalability, and data integrity, proposing effective mitigation strategies. - Contribute to the continuous improvement of data platforms, engineering processes, and team best practices. - Write and maintain clear technical documentation for data pipelines, schemas, and data lineage. - Communicate clearly with team members and clients, proactively raising questions and concerns when requirements or priorities are unclear. Requirements - Professional experience as a Data Engineer working with production-grade data pipelines. - Strong experience with SQL, including query optimization, indexing, partitioning, and understanding performance trade-offs. - Professional experience writing Pythonfor data transformations, following good software design and modularization practices. - Experience designing and implementing data models for analytics and reporting use cases. - Experience building and operating data pipelines using cloud-based data platforms. - Previous hands on experience building AI agents. - Experience operating data pipelines, including error handling, monitoring, troubleshooting, and data quality processes. - Knowledge of fundamental data security and governance practices, including access control, data masking, and PII handling. - Ability to deliver less complex tasks independently and handle more complex challenges with appropriate guidance. - Strong sense of ownership, responsibility, and accountability for data workflows and deliverables. - Good organizational and time management skills, with the ability to estimate effort and meet delivery deadlines. - Advanced English level for effective collaboration with global clients and distributed teams. - Team-oriented mindset with strong communication, collaboration, and problem-solving skills. - Hands-on experience with GCP and BigQuery(desirable) Originally posted on Himalayas