We are looking for a Senior Data Software Engineer with Kafka expertise to join our team building a next-generation data platform that spans a wide portfolio of Oil & Gas products. This is not a role for someone who wants a clean, greenfield problem. Our landscape includes diverse data sources, varying schemas, legacy systems, and operational realities that require someone who can think strategically about how data fits together across products, not just within one. You will be central to how we unify data across our product suite, designing the models, contracts, and real-time data pipelines that make cross-product reporting, AI readiness, and data observability possible. This role also owns our event-streaming backbone, serving as the go-to expert for standing up and administering Apache Kafka as the platform scales. Responsibilities Design and own canonical and semantic data models that create a coherent, product-agnostic view of Oil & Gas data Define the contracts and standards that allow data from disparate products to be stitched together reliably and consistently Tackle the real-world challenge of integrating data across a broad portfolio of O&G applications, each with its own schema, cadence, and business context Identify patterns, resolve conflicts, and build the connective tissue that makes cross-product reporting meaningful Architect, deploy, and administer Apache Kafka clusters as the backbone of real-time and event-driven data flows Own topic and partition design, security configuration, monitoring, capacity planning, and performance tuning across environments Build data foundations ready to support machine learning, LLM-based features, and advanced analytics without requiring a rebuild Instrument data flows to understand how data is being produced, consumed, and relied upon by clients Design and implement usage tracking, lineage, and observability tooling that gives the business visibility into data health and adoption Work closely with product managers, data scientists, and application teams across multiple products Translate complex data challenges into clear models and communicate architectural decisions to both technical and non-technical stakeholders Establish and document data standards, data dictionaries, model documentation, and integration specs that allow the team and the business to reason about data with confidence Requirements Expertise in Apache Kafka, including standing up clusters from scratch and administering them in production, broker configuration, topic and partition design, replication, SASL/SSL security, ACLs, schema registry, monitoring/alerting, and performance tuning at scale 5+ years of experience in data engineering with a strong focus on data modeling and integration across complex, multi-source environments Expertise in canonical and semantic data modeling, with the ability to design models that serve multiple consumers without being owned by any single one Proven ability to integrate data across heterogeneous systems, different schemas, frequencies, and business contexts, into coherent, queryable assets Proficiency in SQL and Python applied to production data engineering, not just exploration Experience designing for downstream use, such as reports, analytics, and AI/ML, with an understanding of how modeling decisions today create constraints or enablement tomorrow Strong written communication skills, capable of producing documentation and data contracts that others can operate from without hand-holding Demonstrated ability to work autonomously and drive work forward in ambiguous, evolving environments Nice to have Background in Oil & Gas, energy, or industrial/operational data environments, understanding the domain challenges of production, measurement, and asset data Familiarity with data observability and telemetry patterns, including lineage tracking, usage instrumentation, and data quality monitoring
