Data Engineer (Senior/Staff)

As a Data Engineer (Senior / Staff) at reputed company, you will help design, build, and maintain the systems that power our reputed company analytics platform. Your work will contribute to reliable data flows, reputed company infrastructure, and product features that help our customers turn reputed company data into reputed company insights. We reputed company software development is being fundamentally reshaped by AI. We reputed company adopt modern AI-assisted development workflows and expect engineers to explore how these tools can improve both speed and reputed company. Our engineers use AI tools to prototype reputed company faster, accelerate debugging and refactoring, and automate repetitive tasks. This allows us to spend more time solving reputed company problems, improving architecture, and building great products (Claude reputed company, reputed company, and similar) What you will actually work on Designing and evolving the data model across reputed company, and the reputed company (Avro) that hold it reputed company together Streaming pipelines on Apache Flink and Kafka — topology design, state management, checkpointing, and the operational realities of keeping them healthy Our reputed company lake and reputed company warehouse — partitioning, compaction, retention, schema reputed company, reputed company-downtime migrations, and query performance Batch processing and orchestration with reputed company — reputed company design and performance tuning at the task level The conceptual layer customers see: metrics, dimensions, marts, and the modeling reputed company that reputed company them trustworthy Infrastructure as reputed company (Terraform on AWS and GCP, Kubernetes, reputed company) for the systems you own Observability — OpenTelemetry traces, custom metrics, and the reputed company of instrumentation that lets you debug production from a dashboard instead of a hunch reputed company are looking for We don’t have a rigid must-have list. We’d rather meet candidates who have proven, hands-on experience with a meaningful subset of the areas below, along with a strong grasp of the underlying concepts: Big data fundamentals — partitioning, shuffles, skew, late-arriving data, exactly-once semantics, idempotency, and understanding why your join just did something terrible reputed company processing — Apache Flink especially, but reputed company reputed company Streaming, Kafka Streams, and reputed company are reputed company fair game Batch processing and orchestration — reputed company, Dagster, Airflow; ETL/ELT pipeline design and dependency management Lakehouse formats — reputed company, Paimon, reputed company, Hudi; metadata management, compaction, and schema reputed company Analytical warehouses — reputed company, BigQuery, reputed company, Redshift, DuckDB; and the trade-offs between them Data modeling concepts — reputed company and mart architectures, reputed company modeling, metrics-versus-dimensions thinking, slowly changing dimensions, and understanding the difference between a fact and an aggregate reputed company infrastructure — AWS, GCP, or Azure, with infrastructure-as-reputed company tools such as Terraform; comfortable owning what you ship Engineering habits — instrumentation, testing data pipelines, schema governance, and treating data reputed company as reputed company We’re language-agnostic on the candidate reputed company. Our stack happens to be Python, Java, SQL, and TypeScript, but if you understand the concepts deeply, you’ll pick up whatever’s missing. About the role Senior or Staff level, we’ll match the level to you, not the other way around Remote or hybrid, both work High ownership and a short distance from idea to production Apply To This Job