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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and managing data pipelines, ensuring low-latency performance, and maintaining data integrity across large-scale systems. Proficient in data contract establishment and guiding teams through format transitions while optimizing storage and query efficiency.
Highest-signal resume keywords
Data Pipeline DevelopmentLow-Latency StreamingC++ ProficiencySQL ProficiencyData Contract Management
ATS Keywords
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Hard Skills
C++PythonSQLData Pipeline EngineeringData Quality ManagementPerformance MeasurementHigh-Cardinality Schema DesignTelemetry AnalysisAnalytical Query EnginesData Transformation
Soft Skills
Clear CommunicationGood JudgmentProblem-Solving
Tools & Technologies
ClickHouseArrowParquetTelemetry ToolsTime-Series Data
Industry Keywords
Data EngineeringData Storage SystemsEvent IdentityData QualityData Format Changes
Tech Stack
Tools & technologiesPythonSQLC++Go
About the role
Key responsibilities & impact- Develop and construct the store, data model, and query path for engineering performance data
- Ingest, join, store, and deliver data at GPU data-center scale with low latency
- Join profiling data with hosts, schedulers, configuration, logs, and storage context
- Ensure records carry identity and dimensions for comparison across jobs, machines, versions, and time
- Establish and version data contracts with data-producing teams
- Transition consumers through data format changes without disruption
- Balance data quality, query latency, storage cost, and retention
- Measure improvements in efficiency, latency, and resource use
- Handle delayed, duplicated, incomplete, or inconsistent data and expose limitations to downstream users
- Develop data APIs and generated evidence views for human and automated analysis
- Implement access controls and resource limits
- Maintain stable behavior during high demand or failures
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience
- 12+ years of relevant software engineering experience
- Experience delivering and operating data pipelines, storage systems, analytical services, or comparable software used by others
- Experience handling large-scale production data, including billions of events per day or petabyte-class stores
- Experience with low-latency streaming pipelines managing backpressure, replay, and duplicate delivery accurately
- Good judgment about event identity and ordering, data transformations, and effects of errors or missing data
- Ability to explain a concrete performance investigation, including baseline, measurements, competing explanations, changes, verified results, and trade-offs
- Experience establishing and versioning data contracts with producing teams and guiding consumers through format changes
- Ability to debug across component boundaries and validate changes through code review, tests, and independent measurements
- Clear communication about technical choices, observed behavior, and uncertainty
- Proficiency with C++, Python, and SQL
- Hands-on work with telemetry, time-series data, or analytical query engines such as ClickHouse, and columnar formats such as Arrow and Parquet
- Familiarity with profiler data, including trace record formats, sampling semantics, symbolization, clock domains, and aligning events across machines
- Experience with high-cardinality schema design and measured improvements to memory use, storage efficiency, or query performance while preserving correctness
- Track record of making data processing easier to inspect and recover when inputs change, traffic spikes, or failures occur
- Working knowledge of Go
Benefits
Comp & perks- Equity
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