Senior Database Engineer

About Keystone AI Solutions Keystone AI Solutions, a TPG portfolio company headquartered in Columbus, Ohio, is the leading provider of enterprise-wide SaaS solutions for critical network infrastructure. Serving the electric, energy, telecommunications, media, and pipeline industries for over 25 years, Keystone AI blends geospatial data, business intelligence, and AI to deliver 360-degree situational awareness across damage prevention, asset integrity, and land management. Our platform - trusted by Fortune 500 utilities, pipeline operators, and telecom providers - helps customers manage 811 tickets, pipeline integrity data, land rights, and risk, enabling them to improve resilience, reduce risk, and stay ahead of compliance requirements. Role Overview The Senior Database Engineer is a key technical individual contributor who drives the design, development, and evolution of our data management platform. Working closely with the Director of Engineering, solution architects, software engineers, and customer-facing teams, you will shape the database architecture that underpins the AIP/CIM Data Model. You will champion data quality, performance, and scalability across cloud and on-premise environments - and bring deep expertise in pipeline integrity data to help Keystone AI Solutions deliver unparalleled value to its customers. Reporting Structure The Senior Database Engineer will report directly to the Director of Engineering and will collaborate cross-functionally with development, QA, business intelligence, data science, and customer success teams. Key Responsibilities Database Architecture & Design Design and develop robust, scalable data models and database architectures to house and analyze pipeline integrity datasets, including ILI, PODS, GIS (APDM/UPDM), corrosion & CP data, and field NDE data. Establish and enforce data standards, processes, and procedures across teams and products. Drive the evolution of the CIM Data Model to meet current and future customer requirements. Development & Engineering Excellence Implement enhancements to the existing data management platform, supporting new features from design through QA sign-off. Write high-quality stored procedures, queries, and database migration scripts with a focus on performance and maintainability. Diagnose and resolve database performance bottlenecks; partner with software engineers to address data-related issues and system design challenges. Adopt and champion best practices in testing, data integrity validation, documentation, and agile development. Maintain a reusable library of data model documents, templates, and technical guides. Collaboration & Customer Engagement Work directly with customers and subject matter experts to understand existing pipeline integrity data systems, pain points, and integration requirements. Analyze customer GIS and third-party systems to plan and execute integrations with the Keystone AI Solutions platform. Partner with product managers, business analysts, and customer account executives during onboarding and support cases involving customer data. Provide technical guidance to junior engineers and contribute to a culture of continuous improvement. Requirements Required 5+ years of experience in database engineering, data architecture, or a closely related technical role. Expert-level proficiency in SQL and relational database systems - Microsoft Azure SQL and/or SQL Server strongly preferred. Databricks - experience with the Databricks Lakehouse platform for large-scale data engineering, Delta Lake. Python - scripting for data processing, automation, ETL pipelines. Significant hands-on experience with pipeline integrity data including ILI, PODS, GIS platforms (APDM, UPDM), corrosion & CP databases, and field NDE data. Deep knowledge of data modelling, schema design, indexing strategies, and query performance tuning. Experience with stored procedures, views, triggers, and database automation. Familiarity with pipeline integrity business processes and regulations (e.g., CFR 192 & 195, ASME B31.8S). Experience working in agile/scrum software development environments. Excellent analytical and communication skills - able to translate complex data challenges into clear solutions. Self-directed and comfortable working remotely; willingness to travel to customer sites as required. Preferred Claude AI / Anthropic APIs - experience integrating large language models into data workflows, tooling, or internal applications. Agentic AI - familiarity with building or working alongside AI agents for autonomous data analysis, anomaly detection, or decision support within engineering or integrity management contexts. Power BI or SQL Server Reporting Services (SSRS) for building analytical dashboards and reports. Experience with cloud-native data services (Azure Data Factory, Synapse Analytics, or equivalent). Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Originally posted on Himalayas