Ocient

Customer Support

• Support both On-Premise solutions (Physical & Cloud) and Ocient managed customer solutions in a Linux/Unix Environment.
• Perform the administration and monitoring of Ocient Managed Database Solutions.
• Contribute to a customer-facing knowledge base.
• Create and maintain documentation for all major installations and implementations.
• SQL/Query Performance Troubleshooting and Tuning.
• Leverage strong technical skills and equally strong customer service skills to assist customers through diagnosis and resolution of complex problems in a distributed system environment.
• Respond to customer questions regarding technical solutions through phone calls, help tickets, and email On-call support rotations.
• Effectively manage multiple issues while providing timely responses and meeting Service Level objectives.
• Access data center (remotely) in diagnosing customer issues.
• Assist in the onboarding, training, installation, and buildout of customer deployments.
• Provide product feedback to the engineering team for continuous improvement of the product.
• Work directly with customers and represent Ocient with a positive attitude.
• Represent key customers' issues, needs, and business goals.
• Develop a strong understanding of the Ocient product.
• Provide detailed Root Cause Analysis and Corrective Action Plans.
• Issue reproductions, fix, and workaround validation.
• Aid in customer and internal support process and tooling evolution.
• Create tools to be used by support professionals and customers in day-to-day activity.
• Communicate quality & product trends to internal organizations.
• Improve customer support-related processes, procedures, and policies.

Senior Customer Support Specialist – Customer Operations

Machine Learning Engineer

• Design and implement machine learning features used in production customer workflows.
• Help identify and close feature and behavior gaps between our ML capabilities and common frameworks (e.g., Spark ML, scikit-learn).
• Proactively evaluate semantic differences, defaults, and edge cases that could surprise customers.
• Partner with product, architects, and customer-facing teams to anticipate upcoming customer needs and gaps.
• Investigate and resolve issues where ML behavior diverges from user expectations (e.g., model output, metrics, configuration semantics).
• Contribute to other ML initiatives including new models, metrics, performance improvements, and infrastructure work.
• Analyze and improve the performance of existing ML code, balancing correctness and stability with customer facing latency.
• Write clear design docs, tests, and documentation to make behavior explicit and prevent regressions.

Senior Software Engineer – Machine Learning, Geospatial

QA Engineer

• Own end-to-end QA strategy for database connectors and integrations, including JDBC, Python drivers, Single Sign On integrations, and third-party tools including but not limited to Metabase, Tableau, and DBeaver.
• Design and execute functional, performance, stress, and soak tests for client-server I/O paths, network behavior, and large result-set handling.
• Validate query execution correctness and performance when exercised through external clients versus native SQL execution.
• Analyze connector-level performance regressions, including result fetching, pagination, batching, serialization/deserialization, compression, and network utilization.
• Develop and maintain automated test frameworks (primarily in Java and Python) for connector validation, regression coverage, and performance baselining.
• Design and execute benchmarks to evaluate the performance impact of different indexing strategies, including their interaction with query execution, connector-driven access patterns, and I/O behavior across representative workloads.
• Debug complex failures involving client drivers, networking, serialization formats, protocol mismatches, and server-side execution paths.
• Partner closely with Software Engineers across Connectors, Query Processing, I/O, and Storage teams to isolate root causes and validate fixes.
• Review execution plans, logs, metrics, and traces to assess correctness and performance impact.
• Act as a quality gate for connector and I/O-related features prior to release, including customer-driven fixes and escalations.

Senior Software QA Engineer – Connectors, I/O Performance

Full-stack Engineer

• Contribute to the development and optimization of our core database execution engine.
• Work on features that impact query correctness, performance, and scalability.
• Help own and evolve our Bazel-based build system and Buildfarm remote-execution infrastructure while contributing broadly to developer tooling and automation.
• Responsible for ingesting data into the Ocient system at high speeds, enabling massive-scale data solutions.

Software Engineer II

• Help scale teams working on Distributed Systems and Machine Learning initiatives
• Own and evolve Bazel-based build system and Buildfarm remote-execution infrastructure while contributing broadly to developer tooling and automation

Senior Software Engineer

• Own complex ML initiatives from end to end
• From problem definition and model design through deployment and iteration in production
• Mentor other engineers and influence technical direction on model architecture and performance
• Ensure ML solutions are robust, efficient, and aligned to real customer needs

Staff Software Engineer

Engineer

• Own Bazel build configurations, custom rules, and language toolchains for C++, Java, Python, and TypeScript.
• Operate and harden the Buildfarm remote-execution service: monitoring, incident response, performance tuning, and capacity planning.
• Build automation and services (primarily using Python) to integrate Bazel with CI and developer workflows.
• Maintain developer and test tooling (Github Actions workflows and runners, development environments) and the automation that keeps them reproducible.
• Produce documentation for future maintainers and concise runbooks for developers.

Build and Tools Engineer II

Data Engineer

• Develop, enhance, and troubleshoot Mainframe batch processes using JCL, Easytrieve, and SAS.
• Build and maintain automation and data processing scripts using Python.
• Support distributed data processing workloads using Apache Spark and the PySpark API.
• Write efficient SQL queries for data extraction, analysis, and transformation.
• Work with Google Cloud Platform (GCP) services - primarily Cloud Storage - for data movement and storage management.
• Collaborate with data analysts, engineers, and business teams to support data initiatives and enhance data workflows.
• Participate in documentation, code reviews, and best practices for data and code quality.
• Investigate data issues, perform root-cause analysis, and implement corrective actions.

Data Engineer – Mainframe to Cloud Modernization

• Design and execute comprehensive test plans and automated suites to validate new features/optimizations for query processing component of the product
• Develop, run, and analyze regression tests targeting the system-level database functionality — ensuring functional stability, scalability, and performance
• Collaborate strongly with Development team to implement tests onto nightly CI/QA infrastructure, improve existing test coverage and analysis tooling for Query Processing components
• Own end-to-end evaluation of database query processing, partnering across teams to identify behavioral/functional issues, correctness gaps, and opportunities for performance optimization
• Provide technical leadership in defining test strategies, frameworks, and best practices for validating complex query optimization and execution scenarios
• Work cross-functionally with engineering leadership and internal stakeholders to align on feature design goals, ensure test completeness, and drive timely resolution of issues
• Lead the evolution of database testing infrastructure to support scalability, reliability, and reproducibility across functional and system-level query processing tests
• Act as a subject matter expert in query processing functionality, partnering with customer operations and development teams on escalated issues and validation
• Build reproductions of poorly performing customer workloads to investigate issues along with the query processing team on root cause analysis
• Mentor junior engineers, fostering expertise in database query processing and functional testing methodologies.