• Design and build scalable, well-tested DBT models. • Develop and maintain scalable ELT pipelines, ensuring observability and reliability across workflows while leveraging multiple languages and frameworks. • Write performance-aware SQL, understand query execution, and identify and resolve bottlenecks in queries and pipelines. • Improve existing patterns in the codebase and establish new ones. • Partner with product managers, engineers, and stakeholders to understand data needs and provide actionable paths forward. Work closely with engineers across teams to resolve dependencies, facilitate alignment on technical decisions, and mentor other engineers. • Document logic, business rules, and methodology to promote transparency and enable teammates to reference and build on your work.

• Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets. • Define the technical vision for DC data architecture, mentor engineers, and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs. • Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.

• Design, develop, test, and maintain AI/ML models and pipelines powering ExtraHop's products. • Monitor, evaluate, refine, and optimize algorithms to improve accuracy and reduce false positives for model-based behavioral detectors. • Participate in agile development processes, code reviews, and technical strategy discussions. • Collaborate with cross-functional teams to ensure that AI/ML features are integrated seamlessly into the broader product architecture. • Provide technical leadership to junior team members and leverage design and mentorship experience to enable the broader team. • Act as a technical expert, fostering a culture of excellence, curiosity, and collaborative problem solving. • Write clean, maintainable, and efficient code while adhering to best practices. • Address technical debt proactively, continually improving our codebase and technical stack. • Stay current on the latest cybersecurity threats, trends, and technologies to contribute to product enhancements. • Assist in the documentation of product features, technical specifications, and engineering guides.

Role Description We at Coforge are hiring a Mid Data Engineer (#21819) with the following skill set. - Design, develop, and maintain scalable data pipelines and data processing solutions on AWS. - Build and optimize data ingestion, transformation, and storage processes to support business needs. - Collaborate with cross-functional teams to ensure data quality, reliability, and availability. - Monitor, troubleshoot, and improve the performance of data platforms and workflows. Qualifications - 3+ years of experience in Data Engineering or related roles. - Hands-on experience with AWS services such as DynamoDB, Athena, S3, and related data technologies. - Strong programming skills in Python. - Advanced SQL skills for data extraction, transformation, and analysis. - Experience working with Git and version control best practices. - Understanding of ETL/ELT processes and data integration concepts. - Experience working with structured and semi-structured data. - Strong analytical and problem-solving skills. - Ability to work collaboratively in Agile environments. - Good communication skills and attention to detail. Requirements - Experience with additional AWS analytics and data services. - Familiarity with data modeling and data warehousing concepts. - Knowledge of CI/CD practices and automation. - Experience with monitoring and performance optimization of data pipelines. - Exposure to cloud-native architectures and modern data platforms. Company Description At Coforge, we hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.